ArticleFrontiers in immunology2026
A comprehensive prognostic model for older patients with advanced non-small cell lung cancer receiving immunotherapy: a multicenter real-world study.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Older patients (aged ≥ 75 years) with advanced non-small cell lung cancer (NSCLC) receiving immunotherapy represent a growing but understudied population, yet few tools incorporate multidimensional host factors that influence prognosis. We therefore developed and externally validated a real-world prognostic model using bedside-available clinical variables, and compared its performance against conventional indices. Methods: This multicenter retrospective study included patients aged ≥ 75 years with advanced NSCLC receiving first-line immunotherapy. Cox regression analyses were performed to identify potential survival-associated host variables. A composite model, based on clinically relevant candidate variables identified through univariate screening, was developed using endpoint-specific L2-penalized Cox regression and internally validated with 1,000 bootstrap resamples. The final model was externally validated in two independent cohorts. Model performance was assessed using Harrell's C-index, inverse probability of censoring-weighted (IPCW) cumulative/dynamic area under the curve (AUC), calibration, decision curve analysis, and Kaplan-Meier survival analysis with log-rank tests. The model was formally compared with conventional indices using paired bootstrap analyses. Results: A total of 241 patients were included, with 115 in the development cohort and 126 in the pooled external validation cohort. We developed the CALI (Comorbidity-Advanced Lung Cancer Inflammation Index) model integrating comorbidity burden (hypertension, diabetes, chronic obstructive pulmonary disease), recent weight loss, and inflammatory-nutritional status represented by ALI. In the development cohort, 1- and 2-year AUCs were 0.587 and 0.712 for overall survival (OS), 0.584 and 0.708 for progression-free survival (PFS), with significant stratification for OS ( Conclusion: CALI provided modest prognostic discrimination and risk stratification in older patients with advanced NSCLC receiving immunotherapy, with stronger and more consistent performance for OS than for PFS. The model offers a simple, bedside-applicable tool using routinely available clinical variables, and can be easily accessed via our online calculator (https://jccclv.github.io/CALI-calculator) for individualized risk stratification.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.