Dynamic evaluation of postoperative survival in pancreatic ductal adenocarcinoma

The pancreatic ductal adenocarcinoma has a high degree of malignancy, and traditional prognostic assessment methods have limited evaluative capacity. This study is based on the Kallikrein-related peptidase 7 (KLK7) expression and uses conditional survival algorithms to perform dynamic survival assessments of patients. The Cox proportional hazards model was employed for identifying and adjusting for potential confounders. The Kaplan-Meier technique was utilized to estimate the overall survival rate. The computation of the likelihood of patients surviving an additional year after X years of survival was achieved using the equation CS1 = OS(X + 1)/OS(X). A subgroup analysis based on CS1 was conducted for each individual risk factor. A total of 243 eligible patients were included in the study. Conditioned survival (CS) refers to the years a patient has already survived and the predicted years they are likely to survive in the future, while conducting a time-varying analysis of the factors influencing prognosis. The survival probability assessed by CS1 increased year by year, with the 1-, 2-, and 3-year survival rates rising from 50.4% to 91.2%. In contrast, the actuarial overall survival (OS) decreased from 81.9% at 1 year to 38.6% at 3 years post-surgery. The results of the conditional analysis indicate that patients who survive longer within a certain timeframe have better survival expectations in the future. Adverse factors, including KLK7, have a decreasing impact on survival over time. Conditional survival analysis based on KLK7 can provide more accurate survival predictions for patients who has identified KLK7.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2025-03-21
DOI
https://doi.org/10.1097/md.0000000000041942
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic evaluation of postoperative survival in pancreatic ductal adenocarcinoma

Xinyu Yang, Bowen Zheng, Jun Zheng, Rucheng Yao
Medicine
Pancreatic and Hepatic Oncology Research
article

Dynamic evaluation of postoperative survival in pancreatic ductal adenocarcinoma

Xinyu Yang, Bowen Zheng, Jun Zheng, Rucheng Yao
article en

Abstract

The pancreatic ductal adenocarcinoma has a high degree of malignancy, and traditional prognostic assessment methods have limited evaluative capacity. This study is based on the Kallikrein-related peptidase 7 (KLK7) expression and uses conditional survival algorithms to perform dynamic survival assessments of patients. The Cox proportional hazards model was employed for identifying and adjusting for potential confounders. The Kaplan-Meier technique was utilized to estimate the overall survival rate. The computation of the likelihood of patients surviving an additional year after X years of survival was achieved using the equation CS1 = OS(X + 1)/OS(X). A subgroup analysis based on CS1 was conducted for each individual risk factor. A total of 243 eligible patients were included in the study. Conditioned survival (CS) refers to the years a patient has already survived and the predicted years they are likely to survive in the future, while conducting a time-varying analysis of the factors influencing prognosis. The survival probability assessed by CS1 increased year by year, with the 1-, 2-, and 3-year survival rates rising from 50.4% to 91.2%. In contrast, the actuarial overall survival (OS) decreased from 81.9% at 1 year to 38.6% at 3 years post-surgery. The results of the conditional analysis indicate that patients who survive longer within a certain timeframe have better survival expectations in the future. Adverse factors, including KLK7, have a decreasing impact on survival over time. Conditional survival analysis based on KLK7 can provide more accurate survival predictions for patients who has identified KLK7.

MedicineVol. 104(12)
China Three Gorges University (CN), Yichang Central People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 92%
Pancreatic and Hepatic Oncology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.