Evidence mapPaperPMID 40438490Full record

ReviewThe EPMA journal2025

Monoclonal antibody immune therapy response instrument for stratification and cost-effective personalized approaches in 3PM-guided pan cancer management.

Salem Baldi, Mohammed Alnaggar, Maged Al-Mogahed, Khalil A A Khalil, Xianquan Zhan

Abstract readReview
In one paragraph

Review in The EPMA journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Salem BaldiDepartment of Medical Laboratory Diagnostics, School of Medical Technology, Shaoyang University, Shaoyang, 422000 China.
Mohammed AlnaggarDepartment of Oncology, South Hubei Cancer Hospital, Chibi, Xianning, 437000 Hubei China.
Maged Al-MogahedDepartment of Urology, The First Bethune Hospital of Jilin University, Changchun, 130012 China.
Khalil A A KhalilDepartment of Medical Laboratory Sciences, College of Applied Medical Sciences, University of Bisha, 61922 Bisha, Saudi Arabia.
Xianquan ZhanShandong Provincial Key Laboratory of Precision Oncology, Shandong First Medical University & Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune checkpoint inhibitors (ICIs), such as anti-PD-1, anti-PD-L1, and anti-CTLA-4 therapies, have revolutionized cancer treatment by harnessing the body's immune system to eliminate cancer cells. Despite their considerable promise, the efficacy of ICIs significantly differs based on tumor types and specific patient conditions, highlighting the necessity for personalized approaches in the framework of predictive preventive personalized medicine (PPPM; 3PM). Main body: This review proposes a stratification instrument within the 3PM framework to enhance the therapeutic efficacy of ICIs across Pan-cancer. Predictive approaches need to be utilized to enhance the effectiveness of ICIs. For example, biomarkers such as particular genetic alterations and metabolic pathways provide key information on patient treatment responses. To predict treatment outcomes, uncover resistance mechanisms, and tailor medications, we examine biomarkers including PDL-1 and CTLA4. Focusing on cancers like melanoma, bladder, and renal cell carcinoma, we highlight advances in combination therapies and cellular approaches to overcome resistance. We conducted an analysis of clinical trials and public datasets (TCGA, GEO) to evaluate ICI responses across number of cancer types. Survival analysis employed Kaplan-Meier curves and Cox regression. Pan-cancer analysis shows response rates ranging from 19.8% in bladder cancer to > 39% in melanoma when combination therapy is used, emphasizing the potential of 3PM to improve outcomes. By exploring resistance mechanisms and emerging therapeutic innovations, we propose a cost-effective model for better patient stratification and care. Validation of this model requires standardized biomarkers and prospective trials, promising a shift toward precision oncology. Conclusion: Within the 3PM framework, this review addresses the urgent need for cost-effective stratification tools and adaptive combinatorial strategies to optimize outcomes.

Indexed as

Combination therapiesCost-effective stratification toolImmune checkpoint inhibitorsPan-cancer analysisPersonalized immunotherapyPredictive biomarkersPredictive preventive personalized medicine (PPPM; 3PM; 3P medicine)

Identifiers

PMID40438490
PMCPMC12106254

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.