ArticleAmerican journal of cancer research2026
Efficacy of chemotherapy combined with immune checkpoint inhibitors for advanced non-small cell lung cancer and construction and validation of a prognostic model: a multicenter retrospective cohort study.
Article in American journal of cancer research, 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The goal of this multicenter retrospective cohort study was to determine the efficacy of chemotherapy in combination with immune checkpoint inhibitors (ICIs) as compared to chemotherapy alone in patients with advanced non-small cell lung cancer (NSCLC). Further, the study will assess the efficacy between the PD-1 inhibitors, evaluate independent prognostic factors and build nomogram models for predicting progression free survival (PFS) and overall survival (OS). Clinical data were retrospectively collected from patients of two centers who received first-line treatment between January 2019 and December 2023 (training cohort n=286, external validation cohort n=124). To balance baseline characteristics, propensity score matching (PSM) was adopted. Cox regression analyses were then performed to find the independent prognostic factors. After PSM (propensity score matching), a significantly higher objective response rate and disease control rate were found in the combination therapy group as compared with a single-agent therapy group (both P<0.05). The combination therapy group also exhibited a significantly longer median PFS of 10 months as compared with 6 months of single-agent therapy group; HR=1.92, P<0.001. Similarly, the combination therapy group exhibited significantly longer median OS of 21 months as compared with 12 months of single-agent therapy group; HR=2.07, P<0.001. The effectiveness of tislelizumab was similar to sintilimab in treating multiple cancers, which was further confirmed by network meta-analysis. Based on the multivariate analysis, treatment regimen, serum albumin, age, smoking status, Charlson Comorbidity Index, ECOG performance status, organ metastasis status and number of organ metastasis were independent prognostic factors for PFS, while first six variables (except smoking status and CCI) for OS. The area under the curve (AUC) values for both nomograms in internal and external validation were greater than 0.75, and they showed good calibration, good clinical utility and good risk stratification performances or capabilities. In conclusion, chemotherapy plus ICIs significantly improves short-term efficacy and long-term survival in advanced NSCLC, tislelizumab and sintilimab showed comparable efficacy, and the constructed nomograms could provide some significance for individualized clinical decision-making.
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.