{
  "abstract": "Introduction: 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. Methods: 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 = mortality event; Yes = no 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. Results: Among 1,782 patients, 770 (43.2%) were recorded as survived = No. 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 −0.031 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. Conclusion: 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.",
  "abstract_shown": true,
  "affiliations": [
    "Comilla Medical College, Cumilla, Bangladesh",
    "Tbilisi State Medical University, Tbilisi, Georgia"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Sourov Das"
    },
    {
      "affs": [
        1
      ],
      "name": "Sushmita Kundu"
    },
    {
      "name": "Salma Jahan Tanny"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/erfcxtjg5d5pp.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0359406",
  "fulltext_url": null,
  "id": "erfcxtjg5d5pp",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0359406",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2740|Lung Cancer Diagnosis and Treatment"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Physiological parameters/Body weight/Body mass index"
    ],
    [
      "plos",
      "/Medicine and health sciences/Clinical medicine/Clinical oncology/Cancer chemotherapy"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology/Medical risk factors/Cancer risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancer risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancer treatment"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancer treatment/Cancer chemotherapy"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Cancers and neoplasms/Lung and intrathoracic tumors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Oncology/Clinical oncology/Cancer chemotherapy"
    ],
    [
      "plos",
      "/Medicine and health sciences/Pharmaceutics/Drug therapy/Chemotherapy/Cancer chemotherapy"
    ],
    [
      "plos",
      "/Medicine and health sciences/Surgical and invasive medical procedures"
    ],
    [
      "plos",
      "/People and places/Geographical locations/Asia/Bangladesh"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Forecasting"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Forecasting"
    ]
  ],
  "openalex": "W7221855476",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0359406&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/erfcxtjg5d5pp.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:23Z",
      "native_id": "10.1371/journal.pone.0359406",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0359406"
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  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "plos:oncology",
      "subfield": "oncology"
    }
  ],
  "title": "Stage-driven mortality and clinical risk stratification among lung cancer patients in Dhaka, Bangladesh: A multi-hospital secondary analysis",
  "title_text": "Stage-driven mortality and clinical risk stratification among lung cancer patients in Dhaka, Bangladesh: A multi-hospital secondary analysis",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:23Z",
  "url": "https://research.draconitic.com/paper/erfcxtjg5d5pp",
  "venue": "PLOS One",
  "versions": []
}