{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T17:47:14Z","timestamp":1792086434669,"version":"4.4.0"},"reference-count":27,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Lung cancer is a major cause of cancer mortality, and patient-level outcome data from Bangladesh remain limited. Locally relevant, interpretable risk-stratification models may help identify patients with higher recorded mortality risk using routinely available clinical variables. This study evaluated mortality-associated factors and the hospital-wise internal-external validation performance of a clinical risk-stratification model among lung cancer patients in Dhaka, Bangladesh.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We performed a retrospective secondary analysis of a publicly available, de-identified multi-hospital dataset comprising 1,782 patients. The primary endpoint was recorded binary mortality status, defined from the source variable survived (No\u2009=\u2009mortality event; Yes\u2009=\u2009no recorded mortality event). Multivariable logistic regression was used for association analysis. A hospital-agnostic logistic prediction model was evaluated using leave-one-hospital-out internal-external validation. Discrimination was assessed by the area under the receiver operating characteristic curve (AUROC), calibration by Brier score, calibration intercept and slope, and predicted-risk deciles, and potential clinical utility by decision curve analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 1,782 patients, 770 (43.2%) were recorded as survived\u2009=\u2009No. Recorded mortality increased across cancer stages: 16.3% in Stage I, 32.5% in Stage II, 55.6% in Stage III, and 79.2% in Stage IV. Compared with Stage I, adjusted odds ratios were 2.54 (95% CI 1.86 to 3.46) for Stage II, 6.66 (95% CI 4.86 to 9.14) for Stage III, and 20.77 (95% CI 14.46 to 29.83) for Stage IV. Surgery was associated with lower adjusted odds than chemotherapy (adjusted OR 0.65, 95% CI 0.48 to 0.89). Apparent AUROC was 0.769; pooled leave-one-hospital-out AUROC was 0.753 with a Brier score of 0.198. Pooled calibration yielded an intercept of \u22120.031 and slope of 0.911. At the evaluated 0.05 increments, the model had greater net benefit than treat-all and treat-none strategies from approximately 0.20 to 0.75.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Recorded mortality in this multi-hospital Bangladeshi lung cancer dataset was strongly stage-driven. An interpretable logistic risk model showed moderate discrimination and reasonable calibration across hospital-wise internal-external validation. These findings support further evaluation of routinely available clinical risk stratification, but independent external and prospective validation are required before clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0359406","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T17:24:56Z","timestamp":1792085096000},"page":"e0359406","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Stage-driven mortality and clinical risk stratification among lung cancer patients in Dhaka, Bangladesh: A multi-hospital secondary analysis"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8082-223X","authenticated-orcid":true,"given":"Sourov","family":"Das","sequence":"first","affiliation":[{"name":"Comilla Medical College","place":["Cumilla, Bangladesh"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sushmita","family":"Kundu","sequence":"additional","affiliation":[{"name":"Tbilisi State Medical University","place":["Tbilisi, Georgia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salma Jahan","family":"Tanny","sequence":"additional","affiliation":[{"name":"Comilla Medical College","place":["Cumilla, Bangladesh"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"issue":"3","key":"pone.0359406.ref001","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"F Bray","year":"2024","journal-title":"CA Cancer J Clin"},{"key":"pone.0359406.ref002","author":"International Agency for Research on Cancer","year":"2024"},{"key":"pone.0359406.ref003","doi-asserted-by":"crossref","first-page":"38","DOI":"10.11604\/pamj.2020.35.38.17333","article-title":"The barriers to initiating lung cancer care in low-and middle-income countries","volume":"35","author":"B Lubuzo","year":"2020","journal-title":"Pan Afr Med J"},{"issue":"12","key":"pone.0359406.ref004","doi-asserted-by":"crossref","DOI":"10.1634\/theoncologist.2019-0057","article-title":"Delays and Barriers to Cancer Care in Low- and Middle-Income Countries: A Systematic Review","volume":"24","author":"NR Brand","year":"2019","journal-title":"Oncologist"},{"issue":"9","key":"pone.0359406.ref005","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0257301","article-title":"Duration of intervals in the care seeking pathway for lung cancer in Bangladesh: A journey from symptoms triggering consultation to receipt of treatment","volume":"16","author":"A Ansar","year":"2021","journal-title":"PLoS One"},{"key":"pone.0359406.ref006","article-title":"Lung cancer management in low- and middle-income countries: current challenges and potential solutions","volume":"8","author":"S Jiwnani","year":"2022","journal-title":"JCO Glob Oncol"},{"key":"pone.0359406.ref007","author":"World Health Organization","year":"2019"},{"key":"pone.0359406.ref008","author":"World Bank"},{"key":"pone.0359406.ref009","author":"Health Effects Institute","year":"2024"},{"key":"pone.0359406.ref010","volume-title":"Outdoor air pollution","author":"International Agency for Research on Cancer","year":"2016"},{"key":"pone.0359406.ref011","unstructured":"Paul T, Khan A. A multi-hospital clinical dataset for lung cancer mortality and survival analysis in Dhaka, Bangladesh. 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