Evidence map›Paper›PMID 39433717›Full record

ArticleActa pharmacologica Sinica2025

Longitudinal and time-to-event modeling for the survival of advanced pancreatic ductal adenocarcinoma patients.

Qing-Yu Yao, Ping-Yao Luo, Ling-Xiao Xu, Rong Chen, Jun-Sheng Xue, Ling Yong, Lin Shen, Jun Zhou, Tian-Yan Zhou

Abstract read
In one paragraph

Article in Acta pharmacologica Sinica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Qing-Yu Yao *Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China.
Ping-Yao Luo *Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China.
Ling-Xiao XuDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, Beijing, 100142, China.
Rong ChenDepartment of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China.
Jun-Sheng XueDepartment of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China.
Ling YongDepartment of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China.
Lin ShenDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, Beijing, 100142, China.
Jun ZhouDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, Beijing, 100142, China. joelbmu@126.com.
Tian-Yan ZhouDepartment of Pharmaceutics, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China. tianyanzhou@bjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers especially at advanced stage. In order to analyze the dynamics of potential prognostic biomarkers and further quantify their relationships with the overall survival (OS) of advanced PDAC patients, we herein developed a parametric time-to-event (TTE) model integrated with longitudinal submodels. Data from 104 patients receiving standard chemotherapies were retrospectively collected for model development, and other 54 patients were enrolled as external validation. The longitudinal submodels were developed with the time-course data of sum of longest diameters (SLD) of tumors, serum albumin (ALB) and body weight (BW) using nonlinear mixed effect models. The model-derived metrics including model parameters and individual predictions at different time points were further analyzed in the TTE model, together with other baseline information of patients. A linear growth-exponential shrinkage model was employed to describe the dynamics of SLD, while logistic models were used to fit the relationship of time prior to death with ALB and BW. The TTE model estimated the ALB and BW changes at the 9th week after chemotherapies as well as the baseline CA19-9 level that showed most significant impact on the OS, and the model-based simulations could provide individual survival rate predictions for patients with different prognostic factors. This study quantitatively demonstrates the importance of physical status and baseline disease for the OS of advanced PDAC patients, and highlights that timely nutrition support would be helpful to improve the prognosis.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsAdultAgedBody WeightCA-19-9 AntigenFemaleHumansLongitudinal StudiesMaleMiddle AgedPrognosisRetrospective StudiesSerum AlbuminCA-19-9 AntigenSerum Albuminalbuminbody weightpancreatic ductal adenocarcinomaprognosissurvivaltime-to-event model

Identifiers

PMID39433717
PMCPMC11845622

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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.