OCURRENCIA DE CÁNCER DE PULMÓN DESPUÉS DE UN EPISODIO DE TUBERCULOSIS: REVISIÓN SISTEMÁTICA Y METAANÁLISIS LUNG CANCER OCCURRENCE AFTER AN EPISODE OF TUBERCULOSIS: A SYSTEMATIC REVIEW AND META-ANALYSIS TESIS PARA OPTAR POR EL TÍTULO PROFESIONAL DE MÉDICO CIRUJANO AUTORES JAVIER ALEXANDER CABRERA SANCHEZ VICENTE ALONSO CUBA PAREJA ASESORA LARISSA OTERO VEGAS LIMA - PERÚ 2022 JURADO Presidente: Dr. Sergio Octavio Vasquez Kunze Vocal: Dr. Hector Jesus Sosa Valle Secretario: Dra. Ana Maria Quintana Aquehua Fecha de Sustentación: 08 de noviembre del año 2022 Calificación: Aprobado ASESORA DE TESIS Dra. Larissa Otero Vegas Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia ORCID: 0000-0002-8348-4340 DEDICATORIA A nuestras familias. AGRADECIMIENTOS Agradecemos inmensamente a nuestra asesora por su guía constante durante los últimos dos años. También agradecemos al Dr. Patrick Van der Stuyft y al Dr. Víctor Vega Zambrano, quienes brindaron aportes valiosos al desarrollo de este trabajo. Finalmente, agradecemos al Instituto de Medicina Tropical Alexander von Humboldt por el apoyo durante el desarrollo de nuestra tesis y por la difusión de los resultados de nuestra investigación. FUENTES DE FINANCIAMIENTO El estudio recibió el apoyo financiero del acuerdo marco de colaboración institucional lV entre el Instituto de Medicina Tropical Amberes, Bélgica y el Instituto de Medicina Alexander Von Humboldt, Universidad Peruana Cayetano Heredia, Perú. L. Otero cuenta con el apoyo de un premio de líder mundial emergente del Centro Internacional Fogarty en los Institutos Nacionales de Salud (K43TW011137). Rol de la fuente de financiación: la fuente de financiación no tenía ningún papel en el diseño, la interpretación o la decisión de presentar este manuscrito. DECLARACIÓN DE CONFLICTO DE INTERÉS Los autores declaran no tener conflictos de interés RESULTADO DEL INFORME DE SIMILITUD TABLA DE CONTENIDOS I. Introducción……………...……………………...…………..1 II. Materiales y Métodos……………………......…...…………2 III. Resultados………………………………...……...………….3 IV. Discusión…………………………………....…......………..7 V. Conclusiones………………………………………………...9 VI. Referencias Bibliográficas…………………………………..9 Material Suplementario…………………………………………….14 RESUMEN Antecedentes: La tuberculosis genera efectos de salud a largo plazo más allá de la cura, incluyendo enfermedades respiratorias crónicas. Investigamos si la tuberculosis es un factor de riesgo para el cáncer pulmonar posterior. Métodos: Buscamos en PubMed, Scopus, Cochrane, Latin American and Caribbean Health Sciences Literature y Scientific Electronic Library Online estudios de cohorte y casos-controles con estimados que midan la asociación entre tuberculosis y cáncer pulmonar posterior. Utilizamos el modelo de efectos aleatorios para el metaanálisis. El estudio se registró en Prospero (CDR42020178362). Resultados: De 6240 registros, incluimos 29 estudios de cohorte y 44 casos-controles. El metaanálisis de estimados ajustados por edad y tabaquismo (evaluados cuantitativamente) fue HR 1.51 (IC 95% 1.30–1.76, I2 = 81%; cinco estudios), OR 1.74 (IC 95% 1.42–2.13, I2 = 59%; 19 estudios). La ocurrencia de cáncer pulmonar aumentó en los 2 primeros años después del diagnóstico de tuberculosis (HR 5.01, IC 95% 3.64–6.89; dos estudios), pero luego disminuyó. La mayoría de estudios fueron retrospectivos, tuvieron un riesgo de sesgo moderado a alto y no controlaron para tabaquismo pasivo, exposición ambiental y estado socioeconómico. La heterogeneidad fue alta. Conclusión: Documentamos una asociación entre tuberculosis y la ocurrencia de cáncer pulmonar, particularmente en los primeros 2 años. Algunos casos de cáncer pudieron estar presentes durante el diagnóstico de tuberculosis y no se puede determinar causalidad. Se necesitan estudios prospectivos que controlen factores de confusión clave para identificar qué pacientes con tuberculosis tienen el mayor riesgo, así como enfoques rentables para mitigar dicho riesgo. Palabras clave: tuberculosis, cáncer de pulmón, neoplasia de pulmón, revisión sistemática, metaanálisis ABSTRACT Background: People with tuberculosis experience long-term health effects beyond cure, including chronic respiratory diseases. We investigated whether tuberculosis is a risk factor for subsequent lung cancer. Methods: We searched PubMed, Scopus, Cochrane, Latin American and Caribbean Health Sciences Literature and the Scientific Electronic Library Online for cohort and case–control studies providing effect estimates for the association between tuberculosis and subsequent lung cancer. We pooled estimates through random-effects meta-analysis. The study was registered in PROSPERO (CDR42020178362). Results: Out of 6240 records, we included 29 cohort and 44 case–control studies. Pooled estimates adjusted for age and smoking (assessed quantitatively) were hazard ratio (HR) 1.51 (95% CI 1.30–1.76, I2=81%; five studies) and OR 1.74 (95% CI 1.42–2.13, I2=59%; 19 studies). The occurrence of lung cancer was increased for 2 years after tuberculosis diagnosis (HR 5.01, 95% CI 3.64–6.89; two studies), but decreased thereafter. Most studies were retrospective, had moderate to high risk of bias, and did not control for passive smoking, environmental exposure and socioeconomic status. Heterogeneity was high. Conclusion: We document an association between tuberculosis and lung cancer occurrence, particularly in, but not limited to, the first 2 years after tuberculosis diagnosis. Some cancer cases may have been present at the time of tuberculosis diagnosis and therefore causality cannot be ascertained. Prospective studies controlling for key confounding factors are needed to identify which tuberculosis patients are at the highest risk, as well as cost-effective approaches to mitigate such risk. Keywords: tuberculosis, lung cancer, lung neoplasm, systematic review, meta- analysis 1 EUROPEAN RESPIRATORY REVIEW REVIEW J. CABRERA-SANCHEZ ET AL. Lung cancer occurrence after an episode of tuberculosis: a systematic review and meta-analysis Javier Cabrera-Sanchez 1, Vicente Cuba1, Victor Vega2, Patrick Van der Stuyft3 and Larissa Otero1,2 1Facultad de Medicina, Universidad Peruana Cayetano Heredia, Lima, Peru. 2Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru. 3Dept of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium. Corresponding author: Javier Cabrera-Sanchez ( javier.cabrera@upch.pe) Shareable abstract (@ERSpublications) After an episode of tuberculosis, an individual is more likely to be diagnosed with lung cancer than a person in the general population. This is most marked within the first 2 years after a tuberculosis diagnosis, but a causal relation cannot be ascertained. https://bit.ly/38I4HMc Cite this article as: Cabrera-Sanchez J, Cuba V, Vega V, et al. Lung cancer occurrence after an episode of tuberculosis: a systematic review and meta-analysis. Eur Respir Rev 2022; 31: 220025 [DOI: 10.1183/ 16000617.0025-2022]. Abstract Introduction: People with tuberculosis experience long-term health effects beyond cure, including chronic respiratory diseases. We investigated whether tuberculosis is a risk factor for subsequent lung cancer. Methods: We searched PubMed, Scopus, Cochrane, Latin American and Caribbean Health Sciences Literature and the Scientific Electronic Library Online for cohort and case–control studies providing effect estimates for the association between tuberculosis and subsequent lung cancer. We pooled estimates through random-effects meta-analysis. The study was registered in PROSPERO (CDR42020178362). Results: Out of 6240 records, we included 29 cohort and 44 case–control studies. Pooled estimates adjusted for age and smoking (assessed quantitatively) were hazard ratio (HR) 1.51 (95% CI 1.30–1.76, I2=81%; five studies) and OR 1.74 (95% CI 1.42–2.13, I2=59%; 19 studies). The occurrence of lung cancer was increased for 2 years after tuberculosis diagnosis (HR 5.01, 95% CI 3.64–6.89; two studies), but decreased thereafter. Most studies were retrospective, had moderate to high risk of bias, and did not control for passive smoking, environmental exposure and socioeconomic status. Heterogeneity was high. Conclusion: We document an association between tuberculosis and lung cancer occurrence, particularly in, but not limited to, the first 2 years after tuberculosis diagnosis. Some cancer cases may have been present at the time of tuberculosis diagnosis and therefore causality cannot be ascertained. Prospective studies controlling for key confounding factors are needed to identify which tuberculosis patients are at the highest risk, as well as cost-effective approaches to mitigate such risk. Introduction Tuberculosis is a major health problem worldwide. Although the incidence is slowly declining, an estimated 10 million cases and 1.5 million tuberculosis deaths occurred in 2020 [1]. Its morbidity burden extends beyond cure, since people successfully treated for tuberculosis experience health problems in the long term. Tuberculosis has been associated with subsequent lung function impairment and other respiratory conditions such as bronchiectasis and COPD [2, 3]. All-cause mortality is significantly higher in people treated for tuberculosis compared to the general population [4]. The association between tuberculosis and lung cancer has received special interest. There were 2.2 million new cases and 1.8 million deaths from lung cancer in 2020 [5]. Chronic inflammation can promote tumour growth in different types of cancer and chronic inflammation in the lung has been hypothesised to promote carcinogenesis [6]. Chronic bronchitis and emphysema have been associated with increased risk of lung cancer, independently of tobacco use [7]. Inflammation from pulmonary tuberculosis has also been suspected to contribute to lung cancer development, but studies on the association between an episode of Copyright ©The authors 2022 This version is distributed under the terms of the Creative Commons Attribution Non- Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions@ersnet.org Received: 4 Feb 2022 Accepted: 16 May 2022 mailto:javier.cabrera@upch.pe https://bit.ly/38I4HMc https://doi.org/10.1183/16000617.0025-2022 https://doi.org/10.1183/16000617.0025-2022 mailto:permissions@ersnet.org EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 2 tuberculosis and subsequent lung cancer have shown mixed results. Some found a positive association, while others did not [8, 9]. A 2009 systematic review of epidemiological studies on the subject found a significant increased risk of lung cancer among people with previous tuberculosis, especially for adenocarcinoma [10]. However, most included studies had a case–control design. During the past decade, several cohort studies assessing this relationship have been published. Still, establishing a causal relationship between tuberculosis and lung cancer is challenging, as it is difficult to control for cofounding due to shared risk factors, especially smoking [11]. It is also problematic to ascertain the absence of lung cancer upon tuberculosis diagnosis, at the start of the follow up. Therefore, reverse causation needs to be considered, the more so because lung cancer facilitates activation of latent tuberculosis infection [12]. We appraised in a systematic review the now available evidence that evaluates the association between tuberculosis and subsequent lung cancer occurrence and mortality. Methods We conducted a systematic review and meta-analysis. The population, exposure, comparator, outcome framework was filled out as follows. Population: any population; exposure: tuberculosis; comparator: subjects without tuberculosis; outcomes: lung cancer diagnosis (the main outcome) and lung cancer mortality (the secondary outcome). The protocol was prospectively registered in PROSPERO (ID number: CDR420178362). We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 checklist to report our findings (appendix 1). Search strategy and selection criteria We searched the literature in PubMed, Scopus, Cochrane, Latin American and Caribbean Health Sciences Literature and the Scientific Electronic Library Online using terms related to “tuberculosis” and “lung cancer” (the full search strategy can be found in appendix 2). We manually searched the references cited in the papers included. Full-text peer-reviewed papers reporting on cohort and case–control studies written in English, French or Spanish and published between 1 January 1980 and 1 September 2021 were eligible for inclusion. We withheld studies with a comparator group reporting an effect estimate for the association between tuberculosis and lung cancer diagnosis or lung cancer mortality. Retrieved articles were uploaded to Covidence 2.0. Title and abstract screening as well as full-text reviews were performed in duplicate by two reviewers ( J. Cabrera-Sanchez and V. Cuba). Discrepancies about the inclusion of a study were resolved by consensus or through discussion with a third reviewer (L. Otero). Data extraction and risk-of-bias assessment We extracted data using a pilot-tested standardised form in Covidence. We extracted bibliographic information, study setting, population description, number of participants, methods to ascertain exposure (tuberculosis)/outcomes (lung cancer diagnosis and lung cancer mortality) and results, including number of events per exposure group and unadjusted and adjusted effect estimates of the association between tuberculosis and subsequent lung cancer diagnosis or mortality. We used the option “merge” in Covidence when data concerning the same study was reported in more than one paper, to treat multiple reports as one single study. In these cases, we extracted the effect estimate based on the larger study population. Authors were contacted by email when necessary to obtain relevant information. To assess the risk of bias, we adapted the Newcastle–Ottawa scale for observational studies, maintaining three domains with a total of eight items: representativeness of the study population (four items), comparability of study groups (one item) and ascertainment of exposure (for cohorts), or outcome (for case– control studies) (three items). The full description of the adapted Newcastle–Ottawa scale, the rationale for adaptations and the rules used to reach the overall risk of bias judgment can be found in the supplementary material (appendices 3 and 4). Both the data extraction and the risk of bias assessment were accomplished independently by two reviewers and disagreements were solved with a third reviewer. Statistical analysis We performed a random-effects meta-analysis to pool unadjusted as well as adjusted estimates of the association between tuberculosis and subsequent lung cancer diagnosis or lung cancer mortality. We developed three models. In the first model, we pooled unadjusted estimates extracted from the included studies. In models two and three, we pooled adjusted estimates. Since the variables considered for adjustment varied widely between studies, we pre-defined (as proposed by RILEY et al. [13]) a minimum set of variables for which studies had to adjust in order to be included in the latter models. These variables were age and smoking, for being associated with tuberculosis and constituting the strongest widespread risk factors for http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 3 lung cancer. Smoking could be assessed either qualitatively by smoking status categories (never-, former or current smoker), or quantitatively, when measured by intensity, duration or cumulative amount. In the second model, we pooled studies’ estimates adjusted for at least age and any assessment of smoking. In the third model, we pooled estimates adjusted for at least age and any quantitative assessment of smoking. Estimates from studies restricted to never-smokers were considered to be quantitatively adjusted for smoking. Thus, studies could contribute to more than one model depending on the estimates reported. If a study only reported results stratified by subgroups, we calculated a single pooled estimate. Studies that did not report unadjusted estimates nor estimates adjusted for at least age and smoking were not included in the meta- analyses, but are still part of the descriptive synthesis of the review, except when the data were available to calculate risk ratios or odds ratios for use in model 1. In view of their methodological differences, separate meta-analyses were performed for cohort and case–control studies. For cohort studies, risk ratios, incidence rate ratios and standardised ratios were pooled together with hazard ratios (HRs). We obtained estimates of pooled odds ratios for case–control studies. To explore heterogeneity, we performed stratified meta-analyses. First, for all studies, stratified by overall risk of bias (as assessed by the review team) and then, conditional on data availability, by sex, smoking status and latency. Since effect estimates in never-smokers are free of residual confounding by active tobacco consumption, we did a subgroup analysis restricted to that subpopulation. We performed stratified analysis by time intervals between tuberculosis diagnosis and lung cancer detection (latency) aiming to decrease the possibility of lung cancer being present at time of tuberculosis diagnosis and deal with reverse causality bias. For this stratified analysis, we constructed categories accommodating the heterogeneity of the cut-offs reported. We developed funnel plots and performed the Egger test to assess publication bias. Meta-analysis was done with the meta package version 4.16-2 using R Studio version 4.0.3. Effect measures were calculated with STATA 15.0 (Stata Corp, College Station, TX, USA) and OpenEpi (Centers for Disease Control and Prevention, Atlanta, GA, USA) when studies did not report them directly, but data to do so were available. Results The search yielded 6240 records, 5106 of which we screened after removing duplicates (figure 1). We excluded 4718 records and retained 127 for retrieving the full text. 62 reports fulfilled the inclusion criteria and were included. We identified 18 eligible records from citation searching. Hence, we included a total of 80 records and 73 unique studies. Lung cancer diagnosis was reported in 62 studies: 19 were cohort studies [8, 9, 14–30 ] and 43 were case–control studies [31–72]. Lung cancer mortality was reported in 13 studies: 12 were cohort studies [9, 26, 73–82] and one was a case–control study [83]. Two studies [9, 26] reported both outcomes. Appendix 5 indicates the number of studies included in the different meta-analysis models that pooled the estimates of associations of tuberculosis with subsequent lung cancer diagnosis or mortality. 46 studies originated from Asia, predominantly from China, Taiwan and South Korea (appendix 6); 16 came from North America (USA and Canada); 10 from Europe; and one from Africa. No studies were conducted in Oceania, Latin America or the Caribbean. Only 39 out of 62 and three out of 13 studies addressing diagnosis or mortality, respectively, adjusted somehow for smoking. 12, 25 and 25 studies had low, moderate and high risk of bias, respectively, for the main outcome. Four, one and eight studies were at low, moderate and high risk of bias, respectively, for the secondary outcome. A full description of the included studies and their risk of bias across different domains can be found in the supplementary material (appendices 7 and 8). Sample sizes ranged from 6699 to 15 219 024 (median 29 641, interquartile range (IQR) 304 977) in cohort studies and from 144 to 91 301 (median 1212, IQR 1983) in case–control studies reporting the main outcome. Sample size in studies reporting the secondary outcome ranged from 515 to 1 607 710 (median 19 497, IQR 39 782) in cohort studies and was 1046 in one case–control study. For lung cancer diagnosis, the minimum length of follow-up in cohort studies was 3.8 years and the maximum was 18.5 years (median 8 years, IQR 4 years); for lung cancer mortality, the minimum was 2 years and the maximum 25 years (median 10 years, IQR 7 years). In most cohort studies, lung cancer was detected under routine medical care and coupled to tuberculosis diagnosis through record linkage or by using registries, except in one study [25], where chest radiography was performed systematically as part of the study’s follow-up. Individual results reported in the included studies are tabulated in appendix 9. Results from the meta-analysis are summarised in table 1. For lung cancer diagnosis, among cohort studies, the pooled adjusted hazard ratio for persons with a tuberculosis history versus nonexposed individuals was 1.87 (95% CI 1.29–2.70, I2=94%; figure 2) in model 2 and 1.57 (95% CI 1.20–2.07, I2=74%; figure 3) in model 3. http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 4 FIGURE 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flowchart. LILACS: Latin American and Caribbean Health Sciences Literature; SciELO: Scientific Electronic Library Online. EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 5 There exists heterogeneity, but six out of seven studies that controlled for smoking documented a positive association. Among case–control studies, the pooled adjusted odds ratio was 1.76 (95% CI 1.41–2.19, I2=79%; figure 2) in model 2 and 1.74 (95% CI 1.42–2.13, I2=59%; figure 3) in model 3. Moderate heterogeneity was found, with 20 out of 23 studies included in model 2 documenting a positive association between tuberculosis and subsequent lung cancer diagnosis. The pooled model 2 estimate for lung cancer mortality subsequent to tuberculosis was significant in cohort studies (HR 1.62, 95% CI 1.18–2.21; I2=68%; appendix 10). The pooled estimates of the associations between tuberculosis and specific lung cancer subtypes (table 1) are generally in line with the overall results above, but lack precision. We restricted stratified analyses (table 2) to the main outcome, lung cancer diagnosis, due to the small number of studies (n=2) eligible for inclusion in adjusted models of the secondary outcome. The estimates in the risk of bias strata differ between themselves, but still remain broadly in line with the nonstratified FIGURE 2 Forest plots showing the association between tuberculosis and subsequent lung cancer diagnosis in studies with adjustment for age and any assessment of smoking (model 2). HR: hazard ratio. http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 6 results reported earlier. Results by sex were comparable for men and women. The estimates in never-smokers were significant in both cohort and case–control studies and close to the earlier-obtained estimates in the models including studies that adjusted for smoking. We observed that the risk of lung cancer diagnosis was high in the first years after tuberculosis diagnosis (table 2 and appendix 11), but decreased and became moderate-to-weak over time. Out of the 19 cohort studies reporting the main outcome, 10 did not perform stratified analysis according to the interval between tuberculosis diagnosis and detection of lung cancer nor exclude lung cancer cases detected in the first years of follow-up. Those that did so used variable cut-off points, which constrained our stratified pooled analysis by latency. The pooled hazard ratio adjusted for smoking and age for patients that developed cancer beyond 2 years of tuberculosis diagnosis from the only two studies reporting such effect estimate [17, 25] was 1.44 (95% CI 1.06–1.96; table 2). When we pooled study estimates that excluded lung cancer cases detected within 1 [15] or 2 years [17, 25] of tuberculosis diagnosis the pooled hazard ratio was 1.47 (95% CI 1.10–1.97) (appendix 12). Among the two cohort studies [18, 79] that reported adjusted results for the secondary outcome (lung cancer mortality), one [79] excluded patients who died within the first 2 years of follow-up alongside patients with unconfirmed suspected malignancy (or with recent weight loss) at enrolment. Its adjusted hazard ratio for tuberculosis and death from lung cancer was 2.01 (95% CI 1.40–2.89). FIGURE 3 Forest plots showing the association between tuberculosis and subsequent lung cancer diagnosis in studies with adjustment for age and quantitatively assessed smoking (model 3). HR: hazard ratio. http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 7 Funnel plots of the main outcome do not indicate small-study effects (appendix 13). Egger test was not significant for the main outcome in cohort ( p=0.61) and case–control studies ( p=0.37). These analyses were not performed for the secondary outcome due to the small number of included studies. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) assessment of the evidence (appendix 14) reveals overall low certainty for cohort studies and very low certainty for case–control studies. Discussion This systematic review and meta-analysis found moderate pooled effect estimates for being diagnosed with lung cancer after a tuberculosis episode: adjusted for age and smoking, a hazard ratio of 1.51 (95% CI 1.30– 1.76) in cohort studies and an odds ratio of 1.74 (95% CI 1.42–2.13) in case–control studies. In addition, we found a compatible pooled hazard ratio of 1.62 (95% CI 1.18–2.21) of dying from lung cancer. The pooled hazard ratios and odds ratios for lung cancer occurrence remained consistent with the overall result in a stratified meta-analysis by risk of study bias and sex, and when restricted to never-smokers. The hazard ratio was positive for incidence of adenocarcinoma and squamous cell carcinoma diagnosis but not of small cell carcinoma. Importantly, in cohort studies we found, adjusted for age and smoking, a substantially increased occurrence of being diagnosed with lung cancer within the first 2 years after tuberculosis diagnosis (HR 5.01, 95% CI 3.64–6.89) that waned after year two (HR 1.44, 95% CI 1.06–1.96) and disappeared after 4 years. http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 8 Our crude results are comparable with the overall risk ratio adjusted for smoking (1.74, 95% CI 1.48–2.03) found in a previous review [10], which included 37 case–control and four cohort studies published between 1966 and 2008. However, that review concluded that, while declining much in the first 5 years, lung cancer risk ratio remained at ∼2 for >20 years after a diagnosis of tuberculosis. The overall certainty of evidence provided by the 43 case–control studies included in our review is very low, but most of the 19 cohort studies have moderate risk of bias, good precision and consistent effect estimates. However, the certainty of their accumulated evidence is rated low in the GRADE framework due to their observational nature. While almost all studies included in our review report effect estimates of the association between tuberculosis and subsequent lung cancer greater than one, there exists quite some heterogeneity that is possibly explained by the presence of (residual) confounding. It is of note that 31 out of the 73 studies did not even control for smoking status, while tobacco consumption increases the risk of developing lung cancer >10-fold [84]. However, when limiting our meta-analysis to the studies that controlled at least for smoking and age, or that selected never-smokers, we still found significant, moderately positive pooled hazard ratios and odds ratios. The increased risk of lung cancer thus seems to be independent of active tobacco consumption, but we cannot exclude residual confounding by passive smoking, which has a weaker association to tuberculosis [85]. Furthermore, the studies did generally not adjust for socioeconomic status and environmental pollution, which have also been associated with tuberculosis and lung cancer [11]. Low socioeconomic status is a risk factor for tuberculosis [86] and may be associated with higher exposure to environmental pollution or occupational carcinogens. A meta-analysis found low socioeconomic status to mildly increase the risk of developing lung cancer after adjustment for smoking [87], and the authors hypothesised that both aforementioned exposures were overrepresented among people with lower socioeconomic status. Unfortunately, only two studies included in our review [26, 51] adjusted jointly for the three key confounders: age, smoking and socioeconomic status. Another limitation is that most studies did not conclusively rule out lung cancer upon tuberculosis diagnosis. Not surprisingly, since there are no effective screening methods to detect early or occult lung cancer, with chest radiographs lacking sensitivity and low-dose computed tomography being plagued by false positives [88]. Notwithstanding, the likelihood that occult cancer is present before the tuberculosis diagnoses can be high in retrospective designs and only two included studies were prospective. Furthermore, few studies reported estimates by latency to cancer diagnosis and among those that did, the time category cut-off points used were heterogeneous. This limited our scope for stratified meta-analysis by latency. The substantially higher occurrence of lung cancer we uncovered in the first year (HR 8.50) and first 2 years (HR 5.0) following tuberculosis diagnosis, which fades out thereafter, raises the question whether cancer latency can be that short. The results could be explained by different mechanisms. Firstly, due to shared clinical and radiological characteristics lung cancer can initially be misdiagnosed as tuberculosis, as illustrated by a study in Taiwan [89] that found 1% of such misclassifications. Studies that include tuberculosis cases without bacteriological confirmation may be more prone to this error and most cohort studies in our review selected the exposed comparison group from large national databases or tuberculosis registries but do not clarify what percentage had bacteriological confirmation. Secondly, it is conceivable that occult cancer triggers active tuberculosis occurrence. A recent systematic review found that lung cancer patients are at nine-fold increased risk of developing active tuberculosis [12] and attributed most of the excess risk to the immunosuppressive cancer treatment. Still, people with undiagnosed lung cancer might be at increased risk of active tuberculosis due to cancer by itself having immunomodulatory effects. Excluding lung cancer cases diagnosed within the first 2 years of tuberculosis decreases, but not totally excludes the possibility of lung cancer prevalent cases being already present at the time of tuberculosis diagnosis. In our pooled analysis by latency (table 2), the adjusted hazard ratio for lung cancer diagnosis after ⩾2 years of tuberculosis was 1.44 (95% CI 1.06–1.96). However, it was not significant at ⩾7 years and ⩾10 years. In the three cohort studies [15, 17, 25] that report adjusted stratified analysis according to latency for lung cancer diagnosis, the risk decreased as latency increases (appendix 11). Thirdly, surveillance bias exists if tuberculosis patients are offered, or demand, more medical imaging after diagnosis and further lung conditions may be more likely to be diagnosed. However, regular chest radiography does not seem to increase the diagnostic yield when screening the general population [90]. In the prospective study by SHIELS et al. [25] included in our review, a thorough medical examination with chest radiography was performed at baseline and all participants underwent regular repeat examinations and chest radiography at the same interval during 5–8 years’ follow-up [91]. The overall hazard ratio for lung cancer adjusted for age and smoking in this study was significant and decreased with time after tuberculosis diagnosis. Temporal ambiguity in retrospective designs coupled to the scarcity of prospective studies demonstrating a decreasing relative risk over time has been interpreted as absence of genuine http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 9 relationship between tuberculosis and lung cancer [18]. However, a credible alternative hypothesis would be that the risk dwindles after tuberculosis is cured, analogous to lung cancer hazard progressively decreasing after smoking cessation. We document a modestly increased risk of developing lung cancer after a tuberculosis episode and observe consistency: hazard ratio and odds ratio between 1.5 and 2 in our overall and stratified analyses. Methodological limitations of the reviewed studies warrant a plea for cautious interpretation and preclude a causal reading, but tuberculosis being a risk factor for lung cancer is plausible and coherent. Chronic inflammation in the lung promotes carcinogenesis, in which macrophages may play a role by producing inflammatory cytokines and nitrogen reactive species [92]. This is illustrated by the carcinogenesis in mycobacterium-infected rats depending on the activity of macrophages [93]. Chronic inflammation may also damage DNA and increase mutation rates in key genes that promote malignant cell proliferation and angiogenesis. A study in South Korean patients with pulmonary adenocarcinoma found that the presence of pre-existing tuberculosis lesions was associated with significantly more epidermal growth factor receptor gene mutations [94]. The fragile histidine triad diadenoside triphosphate gene, a tumour suppressor gene, has also been found to be more frequently affected in lung cancer patients with a tuberculosis infection [95]. Evidence is growing on the long-term health consequences of having tuberculosis [96]. This review suggests a potential higher risk of developing lung cancer, which tuberculosis program managers and clinicians ought to be aware of. However, the finding of increased occurrence of lung cancer in the first 2 years after tuberculosis diagnosis could also indicate that some lung cancer cases may have been present at the time of tuberculosis diagnosis, and therefore it is not possible to ascertain causality. Yet, no concrete hard recommendations can be made relating to the programme’s organisation for routine post-cure follow-up, screening and early detection. Notwithstanding, in particular in patients with other risk factors for lung cancer, our result prompt sharpening up clinical suspicion during fortuitous re-encounters and reinforcing the possible ensuing diagnostic work-up. Further basic research is recommended to better understand the biological mechanisms behind the tuberculosis-subsequent lung cancer association. Linking routine tuberculosis programme databases and cancer registers in countries with reliable health information systems, as well as setting up methodologically rigorous longitudinal clinical–epidemiological studies that permit adequate control of potential confounding factors, could enable the identification of which tuberculosis patients (if any) are at the highest risk and for how long. Eventually, operational research will be needed to sort out how health services can cost-effectively contribute to mitigating that risk. Provenance: Submitted article, peer reviewed. Author contributors: J. Cabrera-Sanchez, V. Cuba and L. Otero conceived the study idea. J. Cabrera-Sanchez, V. Cuba, P. Van der Stuyft and L. Otero designed the protocol. J. Cabrera-Sanchez and V. Cuba did the literature search, extracted data and assessed the risk of bias. J. Cabrera-Sanchez and V. Cuba performed the statistical analysis with support from V. Vega and P. Van der Stuyft. J. Cabrera-Sanchez wrote the initial draft of the manuscript. All authors critically revised, provided important conceptual input, and approved the final version of the manuscript. All authors had access to the data. Data sharing: The data supporting this meta-analysis are from previously reported studies and datasets, which have been cited. The extracted data are available in the supplementary material. Conflict of interest: The authors have nothing to disclose. Support statement: The study received financial support from the Institutional Collaboration Framework Agreement lV between the Institute of Tropical Medicine Antwerp, Belgium and Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Peru. L. Otero is supported by an Emerging Global Leader Award from the Fogarty International Center at the National Institutes of Health (K43TW011137). Role of the funding source: The funding source had no role in the design, interpretation, or decision to submit this manuscript. Funding information for this article has been deposited with the Crossref Funder Registry. References 1 World Health Organization (WHO). Global Tuberculosis Report 2021. www.who.int/publications/i/item/ 9789240037021. Date last accessed: 15 November 2021. Questions for future research http://err.ersjournals.com/lookup/doi/10.1183/16000617.0025-2022.figures-only#fig-data-supplementary-materials https://www.crossref.org/services/funder-registry/ http://www.who.int/publications/i/item/9789240037021 http://www.who.int/publications/i/item/9789240037021 EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 10 2 Byrne AL, Marais BJ, Mitnick CD, et al. Tuberculosis and chronic respiratory disease: a systematic review. Int J Infect Dis 2015; 32: 138–146. 3 Fiogbe AA, Agodokpessi G, Tessier JF, et al. Prevalence of lung function impairment in cured pulmonary tuberculosis patients in Cotonou, Benin. Int J Tuberc Lung Dis 2019; 23: 195–202. 4 Romanowski K, Baumann B, Basham CA, et al. Long-term all-cause mortality in people treated for tuberculosis: a systematic review and meta-analysis. Lancet Infect Dis 2019; 19: 1129–1137. 5 Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021; 71: 209–249. 6 Engels EA. Inflammation in the development of lung cancer: epidemiological evidence. Expert Rev Anticancer Ther 2008; 8: 605–615. 7 Brenner DR, Boffetta P, Duell EJ, et al. Previous lung diseases and lung cancer risk: a pooled analysis from the International Lung Cancer Consortium. Am J Epidemiol 2012; 176: 573–585. 8 Littman AJ, Thornquist MD, White E, et al. Prior lung disease and risk of lung cancer in a large prospective study. Cancer Causes Control 2004; 15: 819–827. 9 Engels EA, Shen M, Chapman RS, et al. Tuberculosis and subsequent risk of lung cancer in Xuanwei, China. Int J Cancer 2009; 124: 1183–1187. 10 Liang H-Y, Li X-L, Yu X-S, et al. Facts and fiction of the relationship between preexisting tuberculosis and lung cancer risk: a systematic review. Int J Cancer 2009; 125: 2936–2944. 11 Lin H-H, Ezzati M, Murray M. Tobacco smoke, indoor air pollution and tuberculosis: a systematic review and meta-analysis. PLoS Med 2007; 4: e20. 12 Cheng MP, Abou Chakra CN, Yansouni CP, et al. Risk of active tuberculosis in patients with cancer: a systematic review and meta-analysis. Clin Infect Dis 2017; 64: 635–644. 13 Riley RD, Moons KGM, Snell KIE, et al. A guide to systematic review and meta-analysis of prognostic factor studies. BMJ 2019; 364: k4597. 14 Huang J-Y, Jian Z-H, Nfor ON, et al. The effects of pulmonary diseases on histologic types of lung cancer in both sexes: a population-based study in Taiwan. BMC Cancer 2015; 15: 591. 15 An SJ, Kim YJ, Han SS, et al. Effects of age on the association between pulmonary tuberculosis and lung cancer in a South Korean cohort. J Thorac Dis 2020; 12: 375–382. 16 Bae JM, Li ZM, Shin MH, et al. Pulmonary tuberculosis and lung cancer risk in current smokers: the Seoul Male Cancer Cohort Study. J Korean Med Sci 2013; 28: 896–900. 17 Everatt R, Kuzmickiene I, Davidaviciene E, et al. Incidence of lung cancer among patients with tuberculosis: a nationwide cohort study in Lithuania. Int J Tuberc Lung Dis 2016; 20: 757–763. 18 Hong S, Mok Y, Jeon C, et al. Tuberculosis, smoking and risk for lung cancer incidence and mortality. Int J Cancer 2016; 139: 2447–2455. 19 Jian ZH, Huang JY, Lin FCF, et al. Post-inhaled corticosteroid pulmonary tuberculosis increases lung cancer in patients with asthma. PLoS One 2016; 11: e0159683. 20 Kuo SC, Hu YW, Liu CJ, et al. Association between tuberculosis infections and non-pulmonary malignancies: a nationwide population-based study. Br J Cancer 2013; 109: 229–234. 21 Lai SW, Liao KF, Chen PC, et al. Antidiabetes drugs correlate with decreased risk of lung cancer: a population-based observation in Taiwan. Clin Lung Cancer 2012; 13: 143–148. 22 Liu SF, Kuo HC, Lin MC, et al. Inhaled corticosteroids have a protective effect against lung cancer in female patients with chronic obstructive pulmonary disease: a nationwide population-based cohort study. Oncotarget 2017; 8: 29711–29721. 23 Oh CM, Roh YH, Lim D, et al. Pulmonary tuberculosis is associated with elevated risk of lung cancer in Korea: the nationwide cohort study. J Cancer 2020; 11: 1899–1906. 24 Shebl FM, Engels EA, Goedert JJ, et al. Pulmonary infections and risk of lung cancer among persons with AIDS. J Acquir Immune Defic Syndr 2010; 55: 375–379. 25 Shiels MS, Albanes D, Virtamo J, et al. Increased risk of lung cancer in men with tuberculosis in the alpha- tocopherol, beta-carotene cancer prevention study. Cancer Epidemiol Biomarkers Prev 2011; 20: 672–678. 26 Simonsen DF, Farkas DK, Søgaard M, et al. Tuberculosis and risk of cancer: a Danish nationwide cohort study. Int J Tuberc Lung Dis 2014; 18: 1211–1219. 27 Wu CY, Hu HY, Pu CY, et al. Pulmonary tuberculosis increases the risk of lung cancer: a population-based cohort study. Cancer 2011; 117: 618–624. 28 Wu MF, Jian ZH, Huang JY, et al. Post-inhaled corticosteroid pulmonary tuberculosis and pneumonia increases lung cancer in patients with COPD. BMC Cancer 2016; 16: 778. 29 Yeo Y, Shin DW, Han K, et al. Individual 5-year lung cancer risk prediction model in Korea using a nationwide representative database. Cancers 2021; 13: 3496. 30 Yu YH, Liao CC, Hsu WH, et al. Increased lung cancer risk among patients with pulmonary tuberculosis: a population cohort study. J Thorac Oncol 2011; 6: 32–37. EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 11 31 Alavanja MCR, Brownson RC, Boice JD Jr, et al. Preexisting lung disease and lung cancer among nonsmoking women. Am J Epidemiol 1992; 136: 623–632. 32 Bodmer M, Becker C, Jick SS, et al. Metformin does not alter the risk of lung cancer: a case-control analysis. Lung Cancer 2012; 78: 133–137. 33 Brenner AV, Wang Z, Kleinerman RA, et al. Previous pulmonary diseases and risk of lung cancer in Gansu Province, China. Int J Epidemiol 2001; 30: 118–124. 34 Brenner DR, Hung RJ, Tsao MS, et al. Lung cancer risk in never-smokers: a population-based case-control study of epidemiologic risk factors. BMC Cancer 2010; 10: 285. 35 Brownson RC, Alavanja MC. Previous lung disease and lung cancer risk among women (United States). Cancer Causes Control 2000; 11: 853–858. 36 Chan-Yeung M, Koo LC, Ho JCM, et al. Risk factors associated with lung cancer in Hong Kong. Lung Cancer 2003; 40: 131–140. 37 Cheng MH, Chiu HF, Ho SC, et al. Statin use and the risk of female lung cancer: a population-based case-control study. Lung Cancer 2012; 75: 275–279. 38 Chen GL, Guo L, Yang S, et al. Cancer risk in tuberculosis patients in a high endemic area. BMC Cancer 2021; 21: 679. 39 Galeone C, Pelucchi C, La Vecchia C, et al. Indoor air pollution from solid fuel use, chronic lung diseases and lung cancer in Harbin, Northeast China. Eur J Cancer Prev 2008; 17: 473–478. 40 Hinds MW, Cohen HI, Kolonel LN. Tuberculosis and lung cancer risk in nonsmoking women. Am Rev Respir Dis 1982; 125: 776–778. 41 Hosgood HD III, Chapman RS, He X, et al. History of lung disease and risk of lung cancer in a population with high household fuel combustion exposures in rural China. Lung Cancer 2013; 81: 343–346. 42 Ko YC, Lee CH, Chen MJ, et al. Risk factors for primary lung cancer among non-smoking women in Taiwan. Int J Epidemiol 1997; 26: 24–31. 43 Koshiol J, Rotunno M, Consonni D, et al. Lower risk of lung cancer after multiple pneumonia diagnoses. Cancer Epidemiol Biomarkers Prev 2010; 19: 716–721. 44 Kreuzer M, Gerken M, Kreienbrock L, et al. Lung cancer in lifetime nonsmoking men – results of a case-control study in Germany. Br J Cancer 2001; 84: 134–140. 45 Kreuzer M, Heinrich J, Kreienbrock L, et al. Risk factors for lung cancer among nonsmoking women. Int J Cancer 2002; 100: 706–713. 46 Lai SW, Liao KF, Lin CH, et al. Parkinson’s disease and lung cancer: a population-based case-control study in Taiwan. Geriatr Gerontol Int 2013; 13: 238–240. 47 Lai SW, Lai HC, Lin CL, et al. Statin use and risk of lung cancer in males: a case-control study in Taiwan. Kuwait Med J 2013; 45: 207–210. 48 Lee CH, Ko YC, Cheng LSC, et al. The heterogeneity in risk factors of lung cancer and the difference of histologic distribution between genders in Taiwan. Cancer Causes Control 2001; 12: 289–300. 49 Liang H, Guan P, Yin Z, et al. Risk of lung cancer following nonmalignant respiratory conditions among nonsmoking women living in Shenyang, Northeast China. J Womens Health 2009; 18: 1989–1995. 50 Lim WY, Chen Y, Ali SM, et al. Polymorphisms in inflammatory pathway genes, host factors and lung cancer risk in Chinese female never-smokers. Carcinogenesis 2011; 32: 522–529. 51 Liu Q, Sasco AJ, Riboli E, et al. Indoor air pollution and lung cancer in Guangzhou, People’s Republic of China. Am J Epidemiol 1993; 137: 145–154. 52 Lo YL, Hsiao CF, Chang GC, et al. Risk factors for primary lung cancer among never smokers by gender in a matched case-control study. Cancer Causes Control 2013; 24: 567–576. 53 Luo RX, Wu B, Yi YN, et al. Indoor burning coal air pollution and lung cancer – a case-control study in Fuzhou, China. Lung Cancer 1996; 14: Suppl. 1, S113–S119. 54 Mayne ST, Buenconsejo J, Janerich DT. Previous lung disease and risk of lung cancer among men and women nonsmokers. Am J Epidemiol 1999; 149: 13–20. 55 Osann KE, Lowery JT, Schell MJ. Small cell lung cancer in women: risk associated with smoking, prior respiratory disease, and occupation. Lung Cancer 2000; 28: 1–10. 56 Park SK, Cho LY, Yang JJ, et al. Lung cancer risk and cigarette smoking, lung tuberculosis according to histologic type and gender in a population based case-control study. Lung Cancer 2010; 68: 20–26. 57 Ramanakumar AV, Parent ME, Menzies D, et al. Risk of lung cancer following nonmalignant respiratory conditions: evidence from two case-control studies in Montreal, Canada. Lung Cancer 2006; 53: 5–12. 58 Raspanti GA, Hashibe M, Siwakoti B, et al. Household air pollution and lung cancer risk among never- smokers in Nepal. Environ Res 2016; 147: 141–145. 59 Samet JM, Humble CG, Pathak DR. Personal and family history of respiratory disease and lung cancer risk. Am Rev Respir Dis 1986; 134: 466–470. 60 Schwartz AG, Yang P, Swanson GM. Familial risk of lung cancer among nonsmokers and their relatives. Am J Epidemiol 1996; 144: 554–562. EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 12 61 Seow A, Poh WT, Teh M, et al. Diet, reproductive factors and lung cancer risk among Chinese women in Singapore: evidence for a protective effect of soy in nonsmokers. Int J Cancer 2002; 97: 365–371. 62 Wang SY, Hu YL, Wu YL, et al. A comparative study of the risk factors for lung cancer in Guangdong, China. Lung Cancer 1996; 14: Suppl. 1, S99–S105. 63 Wang TJ, Zhou BS, Shi JP. Lung cancer in nonsmoking Chinese women: a case-control study. Lung Cancer 1996; 14: Suppl. 1, S93–S98. 64 Wang XR, Yu ITS, Chiu YL, et al. Previous pulmonary disease and family cancer history increase the risk of lung cancer among Hong Kong women. Cancer Causes Control 2009; 20: 757–763. 65 Wang X, Hu JF, Tan Y, et al. Cancer stem cell marker Musashi-1 rs2522137 genotype is associated with an increased risk of lung cancer. PLoS One 2014; 9: e95915. 66 Wu AH, Yu MC, Thomas DC, et al. Personal and family history of lung disease as risk factors for adenocarcinoma of the lung. Cancer Res 1988; 48: 7279–7284. 67 Wu AH, Fontham ETH, Reynolds P, et al. Previous lung disease and risk of lung cancer among lifetime nonsmoking women in the United States. Am J Epidemiol 1995; 141: 1023–1032. 68 Wu-Williams A, Dai X, Blot W, et al. Lung cancer among women in north-east China. Br J Cancer 1990; 62: 982–987. 69 Yang L, Lu X, Deng J, et al. Risk factors shared by COPD and lung cancer and mediation effect of COPD: two center case–control studies. Cancer Causes Control 2015; 26: 11–24. 70 Zatloukal P, Kubík A, Pauk N, et al. Adenocarcinoma of the lung among women: risk associated with smoking, prior lung disease, diet and menstrual and pregnancy history. Lung Cancer 2003; 41: 283–293. 71 Zheng W, Blot WJ, Liao ML, et al. Lung cancer and prior tuberculosis infection in Shanghai. Br J Cancer 1987; 56: 501–504. 72 Zhou BS, Wang TJ, Guan P, et al. Indoor air pollution and pulmonary adenocarcinoma among females: a case-control study in Shenyang, China. Oncol Rep 2000; 7: 1253–1259. 73 Boice J, Fraumeni JF. Late effects following isoniazid therapy. Am J Public Health 1980; 70: 987–989. 74 Chen SY, Hayes RB, Liang SR, et al. Mortality experience of haematite mine workers in China. Br J Ind Med 1990; 47: 175–181. 75 Christensen ASH, Roed C, Andersen PH, et al. Long-term mortality in patients with pulmonary and extrapulmonary tuberculosis: a Danish nationwide cohort study. Clin Epidemiol 2014; 6: 405–421. 76 Davis FG, Boice JD, Hrubec Z, et al. Cancer mortality in a radiation-exposed cohort of Massachusetts tuberculosis patients. Cancer Res 1989; 49: 6130–6136. 77 Fløe A, Hilberg O, Wejse C, et al. Comorbidities, mortality and causes of death among patients with tuberculosis in Denmark 1998–2010: a nationwide, register-based case-control study. Thorax 2018; 73: 70–77. 78 Gao YT, Zheng W, Jin F, et al. Retrospective cohort study on association of lung cancer with pulmonary tuberculosis. J Epidemiol 1992; 2: S83–S88. 79 Leung CC, Hui L, Lee RSY, et al. Tuberculosis is associated with increased lung cancer mortality. Int J Tuberc Lung Dis 2013; 17: 687–692. 80 Merlo F, Fontana L, Reggiardo G, et al. Mortality among silicotics in Genoa, Italy, from 1961 to 1987. Scand J Work Environ Health 1995; 21: S77–S80. 81 Ng TP, Chan SL, Lee J. Mortality of a cohort of men in a silicosis register: further evidence of an association with lung cancer. Am J Ind Med 1990; 17: 163–171. 82 Sasaki R, Sakurai R, Aoki K, et al. Cohort study on association of malignant neoplasms among the pulmonary tuberculosis patients in Nagoya TB registry. J Epidemiol 1992; 2: S89–S95. 83 Fu HJ, Gou J. Research on causes of lung cancer: case–control study of 523 cases of lung cancer. Can J Public Health 1984; 75: 161–165. 84 Sasco AJ, Secretan MB, Straif K. Tobacco smoking and cancer: a brief review of recent epidemiological evidence. Lung Cancer 2004; 45: S3–S9. 85 Patra J, Bhatia M, Suraweera W, et al. Exposure to second-hand smoke and the risk of tuberculosis in children and adults: a systematic review and meta-analysis of 18 observational studies. PLoS Med 2015; 12: e1001835. 86 World Health Organization (WHO). Global Tuberculosis Report 2020. 2020. www.who.int/publications/i/item/ 9789240013131. Date last accessed: 15 November 2021. 87 Hovanec J, Siemiatycki J, Conway DI, et al. Lung cancer and socioeconomic status in a pooled analysis of case-control studies. PLoS One 2018; 13: e0192999. 88 Manser R, Lethaby A, Irving LB, et al. Screening for lung cancer. Cochrane Database Syst Rev 2013; 6: CD001991. 89 Shu C-C, Chang S-C, Lai Y-C, et al. Factors for the early revision of misdiagnosed tuberculosis to lung cancer: a multicenter study in a tuberculosis-prevalent area. J Clin Med 2019; 8: 700. 90 Oken MM, Hocking WG, Kvale PA, et al. Screening by chest radiograph and lung cancer mortality: the Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized trial. JAMA 2011; 306: 1865–1873. http://www.who.int/publications/i/item/9789240013131 http://www.who.int/publications/i/item/9789240013131 EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 13 91 ATBC Cancer Prevention Study Group. The alpha-tocopherol, beta-carotene lung cancer prevention study: design, methods, participant characteristics, and compliance. Ann Epidemiol 1994; 4: 1–10. 92 Nalbandian A, Yan BS, Pichugin A, et al. Lung carcinogenesis induced by chronic tuberculosis infection: the experimental model and genetic control. Oncogene 2009; 28: 1928–1938. 93 Li J, Pan Y, Zhang B, et al. Macrophages are needed in the progression of tuberculosis into lung cancer. Tumour Biol 2015; 36: 6063–6066. 94 Hwang K, Paik SS, Lee SH. Impact of pulmonary tuberculosis on the EGFR mutational status and clinical outcome in patients with lung adenocarcinoma. Cancer Res Treat 2019; 51: 158–168. 95 Song L, Yan W, Zhao T, et al. Mycobacterium tuberculosis infection and FHIT gene alterations in lung cancer. Cancer Lett 2005; 219: 155–162. 96 van Kampen SC, Wanner A, Edwards M, et al. International research and guidelines on post-tuberculosis chronic lung disorders: a systematic scoping review. BMJ Glob Health 2018; 3: e000745. EUROPEAN RESPIRATORY REVIEW LUNG CANCER AFTER TB | J. CABRERA-SANCHEZ ET AL. 14 SUPPLEMENTARY MATERIAL LUNG CANCER OCCURRENCE AFTER AN EPISODE OF TUBERCULOSIS: A SYSTEMATIC REVIEW AND META-ANALYSIS AUTHORS Cabrera-Sanchez J, Cuba V, Vega V, Van der Stuyft P, Otero L TABLE OF CONTENTS Appendix 1. PRISMA 2020 checklist Appendix 2. Search strategy Appendix 3. Modified Newcastle-Ottawa Quality Assessment Scale Appendix 4. Rationale for changes to the Newcastle-Ottawa Quality Assessment Scale Appendix 5. Flow diagram of study selection into the meta-analysis models Appendix 6. Summary of the characteristic of the studies included in the systematic review Appendix 7. Characteristics of included studies Table 1. Characteristic of included cohort studies that report lung cancer diagnosis as the outcome Table 2. Characteristic of included case-control studies that report lung cancer diagnosis as the outcome Table 3. Characteristic of included cohort studies that report lung cancer mortality as the outcome Table 4. Characteristic of included case-control studies that report lung cancer mortality as the outcome Appendix 8. Risk of Bias assessment of included studies Table 1. Risk of bias of included cohort studies for the lung cancer diagnosis outcome Table 2. Risk of bias of included case-control studies for the lung cancer diagnosis outcome Table 3. Risk of bias of included cohort studies for the lung cancer mortality outcome Table 4. Risk of bias of included case-control studies for the lung cancer mortality outcome Appendix 9. Results of individual studies Table 1. Effect size estimates of lung cancer diagnosis risk among persons with a previous episode of TB in cohort studies Table 2. Effect size estimates of lung cancer diagnosis risk among persons with a previous episode of TB in case-control studies Table 3. Effect size estimates of lung cancer mortality risk among persons with a previous episode of TB in cohort studies Table 4. Effect size estimates of lung cancer mortality risk among persons with a previous episode of TB in case-control studies Appendix 10. Additional forest plots Figure 1. Forest plot for the association between tuberculosis and subsequent lung cancer diagnosis among cohort studies (model 1) Figure 2. Forest plot for the association between tuberculosis and subsequent lung cancer diagnosis among case-control studies (model 1) Figure 3. Forest plot for the association between tuberculosis and subsequent lung cancer mortality among cohort studies (model 1) Figure 4. Forest plot for the association between tuberculosis and subsequent lung cancer mortality among cohort studies (model 2) Appendix 11. Effect estimates between tuberculosis and lung cancer diagnosis from the three cohort studies included reporting by latency strata Appendix 12. Pooled adjusted estimates from cohort studies excluding lung cancer cases detected within one or two years of tuberculosis diagnosis Appendix 13. Funnel plots Figure 1. Adjusted estimates from cohort studies that report the association between tuberculosis and lung cancer diagnosis Figure 2. Adjusted estimates from case-control studies that report the association between tuberculosis and lung cancer diagnosis Figure 3. Adjusted estimates from cohort studies that report the association between tuberculosis and lung cancer mortality Appendix 14. GRADE assessment of the evidence Appendix 15. List of variables adjusted for in multivariate analyses by included studies Appendix 16. Amendments to the protocol Appendix 17. List of excluded studies with reasons Appendix 1. PRISMA checklist Section and Topic Item # Checklist item Location where item is reported TITLE Title 1 Identify the report as a systematic review. Tittle ABSTRACT Abstract 2 See the PRISMA 2020 for Abstracts checklist. Summary INTRODUCTION Rationale 3 Describe the rationale for the review in the context of existing knowledge. Introduction Objectives 4 Provide an explicit statement of the objective(s) or question(s) the review addresses. Introduction METHODS Eligibility criteria 5 Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses. Methods (Search strategy and inclusion criteria) Information sources 6 Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted. Methods (Search strategy and inclusion criteria) Search strategy 7 Present the full search strategies for all databases, registers and websites, including any filters and limits used. Appendix 2 Selection process 8 Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process. Methods (Search strategy and inclusion criteria) Data collection process 9 Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process. Methods (Data extraction and risk of bias assessment) Data items 10a List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect. Methods (Data extraction and risk of bias assessment) 15 Section and Topic Item # Checklist item Location where item is reported 10b List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information. Methods (Data extraction and risk of bias assessment) Study risk of bias assessment 11 Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process. Methods (Data extraction and risk of bias assessment), Appendix 3 and 4 Effect measures 12 Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results. Methods (Statistic analysis) Synthesis methods 13a Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)). Methods (Statistic analysis) 13b Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions. Methods (Statistic analysis) 13c Describe any methods used to tabulate or visually display results of individual studies and syntheses. Methods (Statistic analysis) 13d Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used. Methods (Statistic analysis) 13e Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, meta-regression). Methods (Statistic analysis) 13f Describe any sensitivity analyses conducted to assess robustness of the synthesized results. Methods (Statistic analysis) Reporting bias assessment 14 Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases). Methods (Statistic analysis) Certainty 15 Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome. Methods 16 Section and Topic Item # Checklist item Location where item is reported assessment (Statistic analysis) RESULTS Study selection 16a Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram. Results, figure 1; Appendix 6 16b Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded. Appendix 16 Study characteristics 17 Cite each included study and present its characteristics. Results; Appendix 7 Risk of bias in studies 18 Present assessments of risk of bias for each included study. Appendix 8 Results of individual studies 19 For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g. confidence/credible interval), ideally using structured tables or plots. Appendix 9 Results of syntheses 20a For each synthesis, briefly summarise the characteristics and risk of bias among contributing studies. Results; Discussion 20b Present results of all statistical syntheses conducted. If meta-analysis was done, present for each the summary estimate and its precision (e.g. confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect. Results; Tables 1 and 2; Appendix 10 20c Present results of all investigations of possible causes of heterogeneity among study results. Table 2 20d Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results. Tables 1 and 2 Reporting biases 21 Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed. Appendix 12 Certainty of evidence 22 Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed. Appendix 13 DISCUSSION Discussion 23a Provide a general interpretation of the results in the context of other evidence. Discussion 23b Discuss any limitations of the evidence included in the review. Discussion 23c Discuss any limitations of the review processes used. Discussion 23d Discuss implications of the results for practice, policy, and future research. Discussion OTHER INFORMATION Registration and protocol 24a Provide registration information for the review, including register name and registration number, or state that the review was not registered. Methods 24b Indicate where the review protocol can be accessed, or state that a protocol was not prepared. Methods 24c Describe and explain any amendments to information provided at registration or in the protocol. Appendix 15 17 Section and Topic Item # Checklist item Location where item is reported Support 25 Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review. Role of the funding source Competing interests 26 Declare any competing interests of review authors. Declaration of interests Availability of data, code and other materials 27 Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review. Data sharing 18 19 Appendix 2. Search strategy Search strategy: PubMed 1. Search tuberculosis[MeSH Terms] 2. Search tuberculosis[Title/Abstract] 3. Search mycobacterium[Title/Abstract] 4. Search "tb"[Title/Abstract] 5. Search "tbc"[Title/Abstract] 6. 1 OR 2 OR 3 OR 4 OR 5 7. Search lung neoplasm[MeSH Terms] 8. Search lung cancer[MeSH Terms] 9. Search lung cancer*[Title/Abstract] 10. Search lung neoplasm*[Title/Abstract] 11. Search lung carcinoma*[Title/Abstract] 12. Search lung tumor*[Title/Abstract] 13. Search pulmonary cancer*[Title/Abstract] 14. Search pulmonary neoplasm*[Title/Abstract] 15. Search pulmonary carcinoma*[Title/Abstract] 16. Search pulmonary tumor*[Title/Abstract 17. Search "cancer of the lung"[Title/Abstract] 18. Search "neoplasm of the lung"[Title/Abstract] 19. Search "tumor of the lung"[Title/Abstract] 20. 7 OR 8 OR 9 OR 10 OR 11 OR 12 OR 13 OR 14 OR 15 OR 16 OR 17 OR 18 OR 19 21. 6 AND 20 22. Search ("case reports"[Publication Type] OR "comment*"[Publication Type] OR "Autobiography"[Publication Type] OR "Biography"[Publication Type] OR "legal case"[Publication Type]) 23. 21 NOT 22 Filters: Publication date from 1980/01/01 to 2020/06/24; English; French; Spanish 20 Search strategy: Scopus 1. TITLE-ABS-KEY ( "tuberculosis" ) 2. TITLE-ABS-KEY ( "mycobacterium infection" ) 3. 1 OR 2 4. TITLE-ABS-KEY ( "lung cancer" ) 5. TITLE-ABS-KEY ( "lung neoplasm" ) 6. TITLE-ABS-KEY ( "lung tumor" ) 7. TITLE-ABS-KEY ( "lung carcinoma" ) 8. TITLE-ABS-KEY ( "lung adenocarcinoma" ) 9. TITLE-ABS-KEY ( "pulmonary cancer" ) 10. TITLE-ABS-KEY ( "pulmonary neoplasm" ) 11. TITLE-ABS-KEY ( "pulmonary tumor" ) 12. TITLE-ABS-KEY ( "pulmonary carcinoma" ) 13. TITLE-ABS-KEY ( "pulmonary adenocarcinoma" ) 14. TITLE-ABS-KEY ( "cancer of the lung" ) 15. TITLE-ABS-KEY ( "cancer of lung" ) 16. TITLE-ABS-KEY ( "neoplasm of the lung" ) 17. TITLE-ABS-KEY ( "neoplasm of lung" ) 18. TITLE-ABS-KEY ( "tumor of lung" ) 19. TITLE-ABS-KEY ( "tumor of the lung" ) ) ) 20. 4 OR 5 OR 6 OR 7 OR 8 OR 9 OR 10 OR 11 OR 12 OR 13 OR 14 OR 15 OR 16 OR 17 OR 18 OR 19 21. 3 AND 20 Filters: 22. LIMIT-TO ( DOCTYPE , "ar" ) 23. LIMIT-TO ( DOCTYPE , "re" ) 24. LIMIT-TO ( DOCTYPE , "le" ) 25. 22 OR 23 OR 24 26. LIMIT-TO ( SUBJAREA , "MEDI" ) 27. LIMIT-TO ( SUBJAREA , "BIOC" ) 28. LIMIT-TO ( SUBJAREA , "IMMU" ) 29. 26 OR 27 OR 28 30. LIMIT-TO ( LANGUAGE , "English" ) 31. LIMIT-TO ( LANGUAGE , "French" ) 32. LIMIT-TO ( LANGUAGE , "Spanish" ) 33. 30 OR 31 OR 32 34. LIMIT-TO ( PUBYEAR , 1980-2021) 35. 25 AND 29 AND 33 AND 34 21 Search strategy: Lilacs 1. tw:(tuberculosis) OR 2. tw:(mycobacterium tuberculosis) OR 3. tw:("TB") OR 4. tw:(mycobacterium infection) 5. 1 OR 2 OR 3 OR 4 6. tw:(lung cancer) OR 7. tw:(lung neoplasm) OR 8. tw:(small cell carcinoma) OR 9. tw:(lung tumor) OR 10. tw:(lung malignancy) OR 11. tw:("cancer of the lung") OR 12. tw:(non-small cell carcinoma) 13. 6 OR 7 OR 8 OR 9 OR 10 OR 11 OR 12 14. 5 AND 13 Search strategy: Scielo 1. ti:(tuberculosis) OR 2. ab:(tuberculosis) OR 3. ti:(TB) OR 4. ab:(TB) OR 5. ti:(mycobacterium infection) 6. ab:(mycobacterium infection) 7. 1 OR 2 OR 3 OR 4 OR 5 OR 6 8. ti:(lung cancer) 9. ab:(lung cancer) 10. ti:(lung neoplasm) 11. ab:(lung neoplasm) 12. ti:(lung tumor) 13. ab:(lung tumor) 14. ti:(lung malignancy) 15. ab:(lung malignancy) 16. 8 OR 9 OR 10 OR 11 OR 12 OR 13 OR 14 OR 15 Search strategy: Cochrane #1: (tuberculosis):ti,ab,kw OR (TB):ti,ab,kw OR ("Mycobacterium"):ti,ab,kw #2: ("lung cancer"):ti,ab,kw OR ("lung neoplasm"):ti,ab,kw OR ("lung adenocarcinoma cell"):ti,ab,kw OR ("small cell lung cancer"):ti,ab,kw OR ("non small cell lung cancer"):ti,ab,kw #3: #1 AND #2 The search strategy was developed by LO (MD, PhD), JACS (medical student) and VC (medical student). 22 Appendix 3. Modified Newcastle-Ottawa Quality Assessment Scale (NOS) Modified Newcastle - Ottawa Quality Assessment Scale Cohort Studies Selection 1) Representativeness of the exposed cohort a) truly representative (one star) b) somewhat representative (one star) c) selected group of users d) no description of the derivation of the cohort 2) Selection of the non exposed cohort a) drawn from the same community as the exposed cohort (one star) b) drawn from a different source c) no description of the derivation of the non exposed cohort 3) Ascertainment of exposure a) Bacteriologically confirmed TB episode, from NTP/medical records (two stars) b) Bacteriologically confirmed episode, from a structured interview (one star) c) Clinically diagnosed TB episode from NTP/medical records (one star) d) Structured interview with no information on bacteriological diagnosis e) Self-report f) No description g) Other 4) Attempt to Demonstrate that outcome of interest was not present at start of study a) yes (excluded cases occurring in the first year after the tuberculosis diagnosis or performed latency analysis) (one star) b) no Comparability 1) Comparability of cohorts on the basis of the design or analysis a) study controls age AND smoking (two stars) b) study controls for age OR smoking (one star) Outcome 1) Assessment of outcome a) Pathological (histological or cytological) diagnosis (for at least 80% of all lung cancer cases) (one star) b) No pathological diagnosis in more than 80% cases. c) No description d) Other 2) Was follow-up long enough for outcomes to occur a) yes (>5 years) (one star) b) no 3) Adequacy of follow up of cohorts a) complete follow up - all subjects accounted for (one star) b) subjects lost to follow up unlikely to introduce bias – number lost less than or equal to 20%, or description of those lost suggested no difference from those followed-up (one star) c) Evidence of selective losses d) Follow-up rate less than 80% and no description of those lost e) No statement Overall risk of bias for cohort studies: Low risk of bias 4 or 5 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome domain Moderate risk of bias 2 or 3 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome domain High risk of bias 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in outcome domain 23 Newcastle - Ottawa Quality Assessment Scale Case Control Studies Selection 1) Is the case definition adequate? a) Yes, with pathological evidence (one star) b) No pathological evidence c) No description 2) Representativeness of the cases a) consecutive or obviously representative series of cases (one star) b) potential for selection biases or not stated 3) Selection of Controls a) community controls (one star) b) hospital controls c) no description 4) Definition of Controls a) no history of disease (lung cancer) (one star) b) no description of source Comparability 1) Comparability of cases and controls on the basis of the design or analysis a) study controls age AND smoking (two stars) b) study controls for age OR smoking (one star) Exposure 1) Ascertainment of exposure a) Linked record with NTP database with bacteriological confirmation (>80%) (two stars) b) Linked record with NTP database without bacteriological confirmation (one star) c) Structured interview where blind to case-control status (one star) d) Interview not blinded or written self-report e) No description 2) Same method of ascertainment for cases and controls a) yes (one star) b) no 3) Non-Response rate a) Similar for both groups and total response rate >80% (one star) b) Non-response selective to one group c) Total response rate <80% d) No description Overall risk of bias for case-control studies: Low risk of bias 3 or 4 stars in selection domain AND 1 or 2 stars in comparability domain AND 3 or 4 stars in exposure domain Moderate risk of bias 2 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 stars in exposure domain High risk of bias 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in exposure domain 24 Appendix 4. Rationale for changes to the Newcastle-Ottawa Scale Cohort studies Original scale Adapted scale Rationale for changes Selection 1 Representativeness of the exposed cohort A. Truly representative (one star) B. Somewhat representative (one star) C. Selected group D. No description of the derivation of the cohort No changes made 2 Selection of the non-exposed cohort A. Drawn from the same community as the exposed cohort (one star) B. Drawn from a different source C. No description of the derivation of the non-exposed cohort No changes made 3 Ascertainment of exposure A. Secure record (e.g., surgical record) (one star) B. Structured interview (one star) C. Written self-report D. No description E. Other Ascertainment of exposure A. Bacteriologically confirmed TB episode, from NTP/medical records (two star) B. Bacteriologically confirmed TB episode, from structured interview (one star) C. Clinically diagnosed TB episode from NTP/medical records (one star) D. Structured interview with no information on bacteriological diagnosis E. Self-report with no further information on the TB symptoms or diagnosis F. No description G. Other When the episode of TB is bacteriologically confirmed, we can be almost certain that it was active TB and not an early manifestation of lung cancer. This is more reliable if it has been ascertained from a NTP or medical record. An interview is less reliable to ascertain if a diagnosis was made bacteriologically Clinical or radiological TB diagnosis is less accurate since TB and lung cancer may share symptoms and radiological findings. 4 Demonstration that outcome of interest was not present at start of study A. Yes, no history of endpoint (one star) B. No 4) Attempt to Demonstrate that outcome of interest was not present at start of study A. Yes (excluded cases occurring in the first year after the tuberculosis diagnosis or performed latency analysis) (one star) B) No Ascertain that a TB patient did not have lung cancer is very difficult to even using imaging. Therefore, we allow for a period one years between the TB diagnosis and the cancer diagnosis. If less, the cancer could have been present. Comparability 25 1 Comparability of cohorts on the basis of the design or analysis controlled for confounders A. The study controls for the most important factor (one star) B. Study controls for any additional important factor (list) (one star) C. Cohorts are not comparable on the basis of the design or analysis controlled for confounders Comparability of cohorts on the basis of the design or analysis controlled for confounders A. The study controls for age AND smoking (two star) B. The study controls for age OR smoking (one star) C. The study controls for other factors only) D. Cohorts are not comparable on the basis of the design or analysis controlled for confounders We considered a study should control for age and smoking for it to be pooled in the adjusted effects meta-analysis. These variables were chosen from a larger list of potential cofounders after considering epidemiological evidence (see “DAG and references”) Smoking and age are the main (ref) risk factors for lung cancer. Studies controlling for both, have more comparable cohorts, than those controlling for age or for other factors only. Outcome 1 Assessment of outcome A. Independent blind assessment (one star) B. Record linkage (one star) C. Self-report D. No description E. Other Assessment of outcome A. Pathological diagnosis (for at least 80% of all lung cancer diagnoses) (one star) B. No pathological diagnosis F. No description G. Other Since TB and lung cancer may share clinical features, we consider it necessary that the diagnosis of lung cancer is made based on pathological evidence. Otherwise, a recurrence or sequel of TB may be misdiagnosed as lung cancer. 2 Was follow-up long enough for outcomes to occur A. Yes (one star) B. No Indicate the median duration of follow-up and a brief rationale for the assessment above:_________________ Was follow-up long enough for outcomes to occur A. Yes (>= 5 years on average) (one star) B. No 26 3 Adequacy of follow-up of cohorts A. Complete follow-up- all subject accounted for (one star) B. Subjects lost to follow-up unlikely to introduce bias – number lost less than or equal to 20% or description of those lost suggested no different from those followed. (one star) C. Follow-up rate less than 80% and no description of those lost D. No statement Adequacy of follow-up of cohorts A. Complete follow-up- all subject accounted for (one star) B. Subjects lost to follow-up unlikely to introduce bias - number lost less than or equal to 20%. (one star) C. losses are clearly selective to one group D. Follow-up rate less than 80% and no description of those lost E. No statement A study where losses are relatively small but selective to one group may also introduce bias. Overall risk of bias Good quality: 3 or 4 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome domain Fair quality: 2 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome domain Poor quality: 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in outcome domain Low risk of bias: 4 or 5 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome domain Moderate risk of bias: 2 or 3 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome domain High risk of bias: 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in outcome domain Adapted to the changes in stars assigned to ascertainment of exposure (because this item can receive up to two stars instead of only one in the original scale). We substituted the terms related to “quality” for “risk of bias” as suggested by current systematic review guidelines. Adapted Newcastle-Ottawa Scale for case-control studies Original scale Adapted scale Rationale for changes Selection 1 Is the case definition adequate? A. Yes, with independent validation (one star) B. Based on record linkage or based on self-reports C. No description Is the case definition adequate? A. Yes, with pathological evidence (one star) B. Attempt to independently validate but not enough pathological evidence C. Based on record linkage D. Based on self-reports E. No description Since TB and lung cancer may share clinical and radiological features, we consider it necessary that the diagnosis of lung cancer is made based on pathological evidence. Otherwise, a recurrence or sequel of TB may be misdiagnosed. 27 2 Representativeness of the cases A. Consecutive or obviously representative series of cases (one star) B. Potential for selection biases or not stated No changes made 3 Selection of Controls This item assesses whether the control series used in the study is derived from the same population as the cases and essentially would have been cases had the outcome been present. A. Community controls (one star) B. Hospital controls or other health service controls C. No description No changes made 4 Definition of Controls A. No history of disease (endpoint) (one star) B. No description of source Definition of Controls A. No history of lung cancer (one star) B. No description of source Comparability 1 Comparability of cases and controls on the basis of the design or analysis controlled for confounders A. The study controls for the most important factor (one star) B. Study controls for any additional important factor (list) (one star) C. Cases and controls are not comparable on the basis of the design or analysis controlled for confounders Comparability of cases and controls on the basis of the design or analysis controlled for confounders A. The study controls* for age AND smoking (two star) B. The study controls* for age OR smoking (one star) C. Study controls* for other predefined factors (socioeconomic status, passive smoking, chronic bronchitis or emphysema) D. Cases and controls are not comparable on the basis of the design or analysis controlled for confounders *if controls were matched to cases, matched analysis needs to be conducted, in order for the factors to be controlled.(not for frequency matching) We considered a study should control for age, and smoking for it to be pooled in the adjusted effects meta-analysis. These variables were chosen from a larger list of potential cofounders after considering epidemiological evidence Exposure 1 Assessment of exposure A. Secure record (one star) B. Structured interview where blind to case/control status (one star) C. Interview not blinded D. Written self-report or medical record only Assessment of exposure A. Linked record with NTP database with bacteriological confirmation (>80%) (two star) B. Linked record with NTP database without When the episode of TB is bacteriologically confirmed, we can be almost certain that it was active TB and not an early manifestation of lung cancer misdiagnosed as TB. Diagnosis of TB based on clinical or radiological criteria is less accurate since TB and lung cancer 28 E. No description bacteriological confirmation (one star). C. Structured interview where blind to case/control status (one star) D. Interview not blinded or written self-report E. No description (bacteriological confirmation of exposure would be ideal, but unlikely to be complete for all) may share symptoms and radiological findings. An interview is less reliable to ascertain if a diagnosis was made bacteriologically and it is also prone to recall bias 2 Same method of ascertainment for cases and controls A. Yes (one star) B. No No changes made 3 Non-response rate A. Same for both groups (one star) B. Non respondents described C. Rate different and no designation Non-response rate (or not possible to link? Which is different to “not linked”) A. Similar for both groups and total response rate >80% and description of non-respondents suggests no difference from respondents. (one star) B. Non-response selective to one group C. Total response rate <80% C. No description A study where overall non- response rate is relatively small but selective to either cases or controls may introduce bias. Overall risk of bias Good quality: 3 or 4 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in exposure domain Fair quality: 2 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in exposure domain Poor quality: 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in exposure domain Low risk of bias: 3 or 4 stars in selection domain AND 1 or 2 stars in comparability domain AND 3 or 4 stars in exposure domain Moderate risk of bias: 2 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 stars in exposure domain High risk of bias: 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in exposure domain 29 Appendix 5. Flow diagram of study selection into the meta-analysis models *Two studies reported both lung cancer diagnosis and mortality as their study outcomes. †Studies that reported an estimate adjusted for variables other than smoking and age (and did not report any unadjusted estimate eligible for model 1). 30 Appendix 6. Summary of the characteristic of the studies included in the systematic review *The variables controlled for in each individual study as well as the number of times each variable was adjusted for by the included studies can be found in appendix 9 and 15. †Either income, education or occupation Cohorts studies (n) Case-control studies (n) Lung cancer diagnosis 19 studies 43 studies Study setting Taiwan (8), South Korea (5), USA (2), China (1), Denmark (1), Finland (1), Lithuania (1) China (16), USA (9), Taiwan (6), Canada (3), Singapore (2), Germany (2), South Korea (1), Nepal (1), Czech Republic (1), Italy (1), United Kingdom (1) Publication date 1980-1999 (0), 2000-2009 (3), 2010-2021 (16) 1980-1999 (14), 2000-2009 (15), 2010-2021 (14) Risk of bias Low (7), moderate (10), high (2) Low (5), moderate (15), high (23) Main variables adjusted for* Smoking (7), age (18), sex (18), any socioeconomic status indicator† (6), any comorbidity (10), passive smoking (0) Smoking (32), age (25), sex (32), any socioeconomic status indicator* (2), any comorbidity (6), passive smoking (6) Lung cancer mortality 12 studies 1 study Study setting China (5), USA (2), Denmark (2), Japan (1), South Korea (1), Italy (1) China (1) Publication date 1980-1999 (7), 2000-2009 (1), 2010-2021 (4) 1980-1999 (1), 2000-2009 (0), 2010-2021 (0) Risk of bias Low (4), moderate (1), high (7) Low (0), moderate (0), high (1) Main variables adjusted for* Smoking (3), age (2), sex (8), any socioeconomic status indicator† (2), any comorbidity (6), passive smoking (1) None Appendix 7. Characteristics of included studies Table 1. Characteristic of included cohort studies that report lung cancer diagnosis as the outcome Study Study setting (location, country) Study population Number of participants Ascertainment of TB / source Comparator group Ascertainment of lung cancer / source Recruitme nt period Follow-up duration Factors adjusted for An et al (2020) South Korea General population, A representative sample established by the National Health Insurance Service (NHIS) 22 656 Only record linkage / NHIS database Five matched people without TB according to the same database Only record linkage / NHIS database 2003-2013 Follow-up until 2013 Adjustment for smoking status (ever smoker, ex-smoker or current smoker), age, sex and household income Bae et al (2013) Seoul, South Korea Representative sample of current male smokers 7 009 Interview / Seoul Male Cancer Cohort (SMCC) Males without history of TB from the same cohort Only record linkage / Seoul Regional Cancer Registry (SRCR), the Korea Central Cancer Registry (KCCR) and death certificates at Statistics Korea 1992-1993 99 965 person-years; follow-up until 2008 Adjustment for age, intake of tomatoes and coffee Engels et al (2009) Xuanwei, China Farmers 42 422 Interview Farmers without history of TB from the same community Death records from hospitals, public security bureaus and public health bureaus 1976-1992 Follow-up until 1996 None Everatt et al (2016) Lithuania General population 21 986 Record linkage / Lithuanian Tuberculosis Registry Estimates from the general population Record linkage ( 66.9% were microscopically confirmed) / Lithuanian Cancer Registry (LCR) 1998-2012 138 811.1 person years; 6.3 years (mean) Standardization for age and sex 31 Hong et al (2016) South Korea General population, participants of the Korean Cancer Prevention Study (KCPS) 1 607 710 Chest x-ray or past hospitalization for TB / National Health Insurance Service (NHIS) Participants without TB that participated in the same study Two or more hospitalizations for lung cancer / NHIS 1997-2000 23 379 734 person-years; 14.5 years (mean) Adjustment for smoking status (current smokers, exsmokers and never-smokers), amount of cigarettes per day (1-9, 10-19 and >=20 ), age, sex, socioeconomic status, alcohol consumption, hospitalizations for respiratory diseases Huang et al (2015) Taiwan General population 15 219 024 Record linkage and more than two outpatient visits or one admission for TB / National Health Insurance Research Database (NHIRD) People without history of TB from the same database Record linkage with histological confirmation / NHIRD, Taiwan Cancer Registry Database (TCRD) 2001-2003 Follow-up until 2008 Adjustment for age, sex, low income, urbanization, geographical area, asthma, COPD, diabetes, hyperlipidaemia, chronic kidney disease, smoking-related cancers Jian et al (2016) Taiwan Asthma patients 54 520 Record linkage and more than two outpatient visits or one admission for TB / NHIRD Asthma patients without history of TB Record linkage with histological confirmation / NHIRD, Taiwan Cancer Registry Database (TCRD) 2001-2005 Follow-up until 2010 Adjustment for age, sex, urbanization, COPD, pneumonia, diabetes, hyperlipidaemia, liver cirrhosis, chronic kidney disease, autoimmune disease, atopy dermatitis, rhinosinusitis, inhaled corticosteroids use, smoking- related cancers Kuo et al (2013) Taiwan General population 6 699 Record linkage including prescription of at least two ant tuberculosis drugs for 2 months / NHIRD Estimates from the general population Record linkage – with histological confirmation / NHIRD, Catastrophic Illness Taiwan Database 2000-2010 28 866 person-years; 3.8 years (median) Standardization for age and sex 32 Lai et al (2012) Taiwan Diabetes Mellitus patients and matched controls (aim of the study was to study diabetes as a risk factor for lung cancer) 98 120 Only record linkage / NHIRD People without history of TB from the same sample Only record linkage / NHIRD 1995-2005 442 237 and 108 214 person-years for the DM and non-DM cohort respectively; follow-up until 2008 Adjustment for age, sex, COPD, diabetes mellitus Littman et al (2004) USA Heavy smokers and asbestos- exposed workers that participated in a cancer prevention trial (CARET trial). 17 698 Interview Subjects without history of TB from the same trial Review of clinical records and pathology reports from the diagnosing physician or hospital to confirm the tumor origin, location, and histology 1985-1993 9.1 years (median); follow-up until 2002 Adjustment for years smoked and years smoked squared, average number of cigarettes smoked per day and average number of cigarettes smoked per day squared, smoking status (former or current), age, sex, body mass index, trial intervention, asbestosis, asthma, chronic bronchitis or emphysema, pneumonia Liu et al (2017) Taiwan Female COPD patients 13 686 Only record linkage / NHIRD Female COPD patients without history of TB from the same database Only record linkage / NHIRD 1997-2011 9.78 years (median); follow-up until 2011 Adjustment for age, income, pneumonia, bronchiectasis, pulmonary fibrosis, hypertension, diabetes mellitus, inhaled corticosteroids use 33 Oh et al (2020) South Korea General population older than 40 years that participated in a nationwide survey (KNHANES study) 20 252 Interview / conducted as part of the survey People without history of TB from the same survey Record linkage with pathological confirmation / Korea Central Cancer Registry 2008-2013 3.85 years (mean) for the TB group, 4 years (mean) for the control group; follow- up until 2014 Adjustment for smoking status (current smokers, ex-smokers or never-smokers), age, sex, income level, education, body mass index, physical activity Shebl et al (2010) USA AIDS patients 322 675 History of TB / HIV/AIDS registries AIDS patients without TB from the same registry Only record linkage / cancer registries in 11 US regions 1977-2002 1 032 256 person-years; 10 years (not clear if mean or median) Adjustment for age, sex, race, mode of HIV acquisition, CD4 count at AIDS onset, calendar year of AIDS onset Shiels et al (2011) Southwester n regions of Finland Male smokers, aged 50 to 69 years old, that participated in a cancer prevention trial (ATBC trial) 29 133 Only record linkage / available from the National Hospital Discharge Register Participants without history of TB from the same trial Record linkage with histology known for 62% cases / Finnish Cancer Registry 1985-1988 Follow-up until 2005 Adjustment for smoking measured with log cig-years (log [cigarettes smoked per day + 1] x number of years smoked) and age Simonsen et al (2014) Denmark General population 15 024 Record linkage (58% cultured- confirmed) / Danish National Registry of Patients (DNRP) Estimates from the general population Record linkage with 89% cases verified morphologically / Danish Cancer Registry, Danish Pathology Register 1978-2011 150 400 person-years; 8.5 years (median) Standardization for age and sex Wu et al (2011) Taiwan General population 29 641 Record linkage and prescriptions of at least 2 anti- tuberculosis medications for >28 day Four matched control subjects with no TB record matched to each TB patient from the same database Record linkage – with histological confirmation / NHIRD, Catastrophic Illness Taiwan Database 1997-2008 5.86 years (mean) for TB patients, 6.22 years (mean) for controls Adjustment for age, sex, COPD, diabetes mellitus, chronic renal failure, autoimmune disease 34 Wu et al (2016) Taiwan COPD patients 44 065 Record linkag