Observational studyPloS one2021
Prediction of outcome in patients with non-small cell lung cancer treated with second line PD-1/PDL-1 inhibitors based on clinical parameters: Results from a prospective, single institution study.
Observational study in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers, 4 of them syntheses that pooled it.
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
21 citing papers in PubMed, 4 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- The use of antibiotic, probiotic, and fecal microbiota transplantation in modulating immunotherapy efficacy and survival: a systematic review and meta-analysis of clinical outcomes.The oncologist · 2026Pooled it
- Pretreatment neutrophil-to-lymphocyte ratio is associated with immunotherapy efficacy in patients with advanced cancer: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- A systematic review and meta-analysis evaluating the impact of antibiotic use on the clinical outcomes of cancer patients treated with immune checkpoint inhibitors.Frontiers in oncology · 2023Pooled it
- The impact of antibiotic use on clinical features and survival outcomes of cancer patients treated with immune checkpoint inhibitors.Frontiers in immunology · 2022Pooled it
- Review
- Artificial intelligence for optimization of immunotherapy: current applications and transformative potential.Frontiers in immunology · 2026Review
- Immunotherapy in the Fight Against Bone Metastases: A Review of Recent Developments and Challenges.Current treatment options in oncology · 2024Review
- A Review of the Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Nonhematologic Malignancies.Diagnostics (Basel, Switzerland) · 2024Review
- Clinical predictors of response to single‑agent immune checkpoint inhibitors in chemotherapy‑pretreated non‑small cell lung cancer.Molecular and clinical oncology · 2024Article
- Antibiotic treatment and survival in non-small cell lung cancer patients receiving immunotherapy: a systematic review and meta-analysis.Translational lung cancer research · 2023Article
- A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning.IBRO neuroscience reports · 2023Article
- Automated machine learning for genome wide association studies.Bioinformatics (Oxford, England) · 2023Article
- Immunotherapy as a potential treatment approach for currently incurable bone metastasis.Journal of bone and mineral metabolism · 2023Review
- Article
- AI/ML advances in non-small cell lung cancer biomarker discovery.Frontiers in oncology · 2023Review
- Review
- A machine learning approach utilizing DNA methylation as an accurate classifier of COVID-19 disease severity.Scientific reports · 2022Article
- Just Add Data: automated predictive modeling for knowledge discovery and feature selection.NPJ precision oncology · 2022Article
- Review
- Proton Pump Inhibitors and Cancer: Current State of Play.Frontiers in pharmacology · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe prospectively recorded clinical and laboratory parameters from patients with metastatic non-small cell lung cancer (NSCLC) treated with 2nd line PD-1/PD-L1 inhibitors in order to address their effect on treatment outcomes. MATERIALS AND
methodsClinicopathological information (age, performance status, smoking, body mass index, histology, organs with metastases), use and duration of proton pump inhibitors, steroids and antibiotics (ATB) and laboratory values [neutrophil/lymphocyte ratio, LDH, albumin] were prospectively collected. Steroid administration was defined as the use of > 10 mg prednisone equivalent for ≥ 10 days. Prolonged ATB administration was defined as ATB ≥ 14 days 30 days before or within the first 3 months of treatment. JADBio, a machine learning pipeline was applied for further multivariate analysis.
resultsData from 66 pts with non-oncogenic driven metastatic NSCLC were analyzed; 15.2% experienced partial response (PR), 34.8% stable disease (SD) and 50% progressive disease (PD). Median overall survival (OS) was 6.77 months. ATB administration did not affect patient OS [HR = 1.35 (CI: 0.761-2.406, p = 0.304)], however, prolonged ATBs [HR = 2.95 (CI: 1.62-5.36, p = 0.0001)] and the presence of bone metastases [HR = 1.89 (CI: 1.02-3.51, p = 0.049)] independently predicted for shorter survival. Prolonged ATB administration, bone metastases, liver metastases and BMI < 25 kg/m2 were selected by JADbio as the important features that were associated with increased probability of developing disease progression as response to treatment. The resulting algorithm that was created was able to predict the probability of disease stabilization (PR or SD) in a single individual with an AUC = 0.806 [95% CI:0.714-0.889].
conclusionsOur results demonstrate an adverse effect of prolonged ATBs on response and survival and underscore their importance along with the presence of bone metastases, liver metastases and low BMI in the individual prediction of outcomes in patients treated with immunotherapy.
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.