ArticleBritish journal of cancer2017
Lung cancer prognostic index: a risk score to predict overall survival after the diagnosis of non-small-cell lung cancer.
Article in British journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.
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Who cites it
47 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Weight loss as a predictor of reduced survival in patients with lung cancer: a systematic review with meta-analysis.International journal of obesity (2005) · 2025Pooled it
- The impact of ECOG performance status on efficacy of immunotherapy and immune-based combinations in cancer patients: the MOUSEION-06 study.Clinical and experimental medicine · 2023Pooled it
- Survival of Squamous Cell Carcinoma Versus Adenocarcinoma in Resected Stage I-III Non-small Cell Lung Cancer.Annals of surgical oncology · 2026Article
- Time-Driven Survival Analysis from FDG-PET/CT in Non-Small Cell Lung Cancer.Annals of biomedical engineering · 2026Article
- The Impact of the COVID-19 Pandemic on Diagnosis, Treatment, and Survival of Lung Cancer Patients in Thailand from 2019-2021.Journal of clinical medicine · 2026Article
- Prognostic performance of a novel multiplex circulating tumor DNA assay for lung cancer outcomes.Therapeutic advances in medical oncology · 2026Article
- Prediction of overall survival in primary lung adenocarcinoma using machine learning and deep learning: a cohort study in Latin America country cancer center.Frontiers in oncology · 2026Article
- Defining the surgical curative time window: identifying patients with an absence of recurrence for 5 years following surgical resection of stage I invasive non-small cell lung cancer.Translational lung cancer research · 2025Article
- Impact of Stage-Specific Guideline Concordant Treatment in Small Cell Lung Cancer in Victoria, Australia.Thoracic cancer · 2025Article
- Integrating ctDNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer.Cancer discovery · 2025Article
- Diverse clinical outcomes for the EGFR‑mutated and ALK‑rearranged advanced non‑squamous non‑small cell lung cancer.Oncology letters · 2025Article
- Population-Adjusted Indirect Treatment Comparisons of Repotrectinib Among Patients withCancers · 2025Article
- Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations.Nature medicine · 2025Article
- Article
- Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought: Algorithm Development and Validation Study.JMIR medical informatics · 2024Article
- Real-World Treatment Patterns and Clinical Outcomes Among Patients with Metastatic or Unresectable EGFR-Mutated Non-Small Cell Lung Cancer Previously Treated with Osimertinib and Platinum-Based Chemotherapy.Advances in therapy · 2024Article
- Molecular alterations and clinical prognostic factors in resectable non-small cell lung cancer.BMC cancer · 2024Article
- Machine learning models for 180-day mortality prediction of patients with advanced cancer using patient-reported symptom data.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023Article
- Deep learning model integrating positron emission tomography and clinical data for prognosis prediction in non-small cell lung cancer patients.BMC bioinformatics · 2023Article
- The Effects of GCSF Primary Prophylaxis on Survival Outcomes and Toxicity in Patients with Advanced Non-Small Cell Lung Cancer on First-Line Chemoimmunotherapy: A Sub-Analysis of the Spinnaker Study.International journal of molecular sciences · 2023Observational
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11 authors.
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No grant is acknowledged in the PubMed record.
Abstract
introductionNon-small-cell lung cancer outcomes are poor but heterogeneous, even within stage groups. To improve prognostic precision we aimed to develop and validate a simple prognostic model using patient and disease variables.
methodsProspective registry and study data were analysed using Cox proportional hazards regression to derive a prognostic model (hospital 1, n=695), which was subsequently tested (Harrell's c-statistic for discrimination and Cox-Snell residuals for calibration) in two independent validation cohorts (hospital 2, n=479 and hospital 3, n=284).
resultsThe derived Lung Cancer Prognostic Index (LCPI) included stage, histology, mutation status, performance status, weight loss, smoking history, respiratory comorbidity, sex, and age. Two-year overall survival rates according to LCPI in the derivation and two validation cohorts, respectively, were 84, 77, and 68% (LCPI 1: score⩽9); 61, 61, and 42% (LCPI 2: score 10-13); 33, 32, and 14% (LCPI 3: score 14-16); 7, 16, and 5% (LCPI 4: score ⩾15). Discrimination (c-statistic) was 0.74 for the derivation cohort, 0.72 and 0.71 for the two validation cohorts.
conclusionsThe LCPI contributes additional prognostic information, which may be used to counsel patients, guide trial eligibility or design, or standardise mortality risk for epidemiological analyses.
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