Evidence map›Paper›PMID 42225935›Full record

ArticleScientific reports2026

Conditional survival patterns and individualized prognostic prediction in malignant peritoneal mesothelioma.

Xiaofeng Liao, Chen Li, Ming Huang, Zheng Yao, Shikun Luo, Xiaoyu Lei

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Xiaofeng Liao *Department of General Surgery, Jiangning Hospital, Hushan Road NO.169, Nanjing, Jiangsu, China.
Chen Li *Department of General Surgery, Jiangning Hospital, Hushan Road NO.169, Nanjing, Jiangsu, China.
Ming Huang *Department of General Surgery, Jiangning Hospital, Hushan Road NO.169, Nanjing, Jiangsu, China.
Zheng YaoDepartment of General Surgery, Jiangning Hospital, Hushan Road NO.169, Nanjing, Jiangsu, China.
Shikun LuoDepartment of General Surgery, Jiangning Hospital, Hushan Road NO.169, Nanjing, Jiangsu, China. doctorlsk1990@163.com.
Xiaoyu LeiDepartment of General Surgery, Jiangning Hospital, Hushan Road NO.169, Nanjing, Jiangsu, China. 1002062945@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Malignant peritoneal mesothelioma (MPM) is a rare, aggressive cancer with limited treatment options and extremely poor survival outcomes. Due to the disease's low incidence, large-scale cohort studies to clarify survival outcomes and the impact of treatments like chemotherapy are limited. This study aimed to use conditional survival (CS) analysis to assess survival trends and explore the survival benefits of chemotherapy in MPM patients. Using SEER data (2000-2019), CS analysis was applied to capture survival probabilities conditional on having survived specific durations after diagnosis. Additionally, we used machine learning algorithms, including Random Survival Forest and the least absolute shrinkage and selection operator regression, combined with Cox proportional hazards models, to develop and validate a nomogram model for CS prediction. Propensity score matching (PSM) was conducted to evaluate the effect of chemotherapy on survival. Among 1,549 MPM patients, CS rates improved with time survived post-diagnosis but plateaued later, highlighting the need for early intervention and follow-up. The CS-based nomogram model demonstrated strong predictive performance, with C-index values of 0.701 and 0.717 in the training and validation cohorts, respectively. The model was well-calibrated, with AUC values indicating consistent predictive accuracy. DCA analysis validated the clinical applicability of the model. PSM analysis showed that chemotherapy was associated with longer overall survival. CS analysis provides a time-updated complement to traditional survival estimates and may inform follow-up intensity and patient counseling. The CS-based nomogram offers a useful adjunct to current staging for individualized risk assessment in MPM. Moreover, our study highlighted the potential survival benefit of chemotherapy, though further research is needed to confirm these findings.

Indexed as

Lung NeoplasmsMesothelioma, MalignantPeritoneal NeoplasmsAgedFemaleHumansMachine LearningMaleMiddle AgedNomogramsPrognosisPropensity ScoreProportional Hazards ModelsSEER ProgramSurvival AnalysisChemotherapyConditional survivalMalignant peritoneal mesotheliomaPrediction modelPrognosis

Identifiers

PMID42225935
PMCPMC13462530

What OpenQuestion 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 OpenQuestion graph.