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A Chemotherapy Progression Decision Score for Treatment Selection After Initial Assessment in Pancreatic Ductal Adenocarcinoma

Journal
MedComm (Q1)
Published
6 August 2026
Study design
Retrospective cohort
Evidence level
Level 3, Low (CEBM 3b)
Authors
Yixin Zhang, Zhongquan Sun, Hongfan Ding, Changlin Zou, Linping Dong, Qi Xu, et al.
PMID
42568817
DOI
10.1002/mco2.70903

Why clinicians should know about it

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with chemotherapy response evaluation currently relying on the Response Evaluation Criteria in Solid Tumors (RECIST). However, RECIST inadequately captures the unique biology of PDAC, particularly stromal fibrosis-induced radiographic pseudoprogression. We developed and externally validated a multivariable prognostic prediction model, the chemotherapy Progression Decision (cPD) score, integrating biological markers and imaging metrics to guide therapeutic decision-making after the first RECIST assessment. This multicenter retrospective study enrolled 616 PDAC patients across three cohorts: the Training Cohort (n = 155), Validation Cohort 1 (n = 263), and Validation Cohort 2 (n = 198). Multivariable Cox regression identified four independent prognostic predictors: neutrophil-to-lymphocyte ratio, baseline carbohydrate antigen 19-9, tumor maximum cross-sectional rate change ratio, and emergence of new lesions. These were integrated into an integer-based score (8-13 points) stratifying patients into good prognosis (GP), poor prognosis (PP), and critical prognosis (CP) groups. The cPD model demonstrated robust discrimination and calibration, with significant survival differences across groups in all cohorts. Notably, the cPD score identified a subset of patients (GP and PP groups) for whom continuing the original chemotherapy yielded significantly better survival than switching regimens, even when RECIST classified the disease as progressive.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.