Background CA19–9 decrease during treatment has been associated with superior survival of pancreatic cancer in several studies. The evidence to show the correlation of high platelet level with inferior survival is insufficient in pancreatic cancer. It also remains unclear whether the association between CA19–9 decrease and survival was corresponded to different levels of platelet in metastatic pancreatic cancer. Methods We measured CA19–9 serum concentration and platelet level at baseline and after the second cycle of chemotherapy for 200 advanced pancreatic cancer patients. A Cox proportional hazards model was used to compute mortality hazard ratios (HRs) for CA19–9 decrease, adjusting for potential confounders, including age, sex, KPS, prediagnosis body mass index, Diabetes Mellitus, tumor location, first-line chemotherapy regimen, and radiotherapy. Results We found that the association of CA19–9 decrease with superior overall survival was stronger in advanced pancreatic cancer with a low level of platelet ( P interaction <  0.001) compared with intermediate and high level of platelet. Multivariable-adjusted hazard ratios per unit decrease of CA19–9 change was 0.45 [95% confidence interval (CI), 0.33 to 0.62] in cases with low platelet level, 0.74 (95% CI, 0.50 to 1.09) in cases with intermediate platelet level, and 0.94 (95% CI, 0.74 to 1.10) in cases with high platelet level. A similar differential association was found between CA19–9 decrease and progression-free survival in strata of platelet level ( P interaction = 0.034). Conclusion The association of CA19–9 decrease with superior pancreatic cancer survival appeared to be pronounced in patients with a low platelet level. This finding could provide supports for the underlying mechanisms of CA19–9 involved in platelet / tumor cell interaction. Electronic supplementary material The online version of this article (10.1186/s12885-019-6078-2) contains supplementary material, which is available to authorized users.

Background Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC. Methods: A total of 323 patients with advanced and metastatic PC were identified from the Chinese People’s Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively. Results In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19–9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19–9, baseline CEA, change in CA 19–9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62–0.71) and 0.74 (95% CI, 0.69–0.77), respectively. Conclusion These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.

PurposePancreatic cancer is an aggressive solid tumor with a severe prognosis. Although tumor biomarkers are often used to identify advanced pancreatic cancer, this is not accurate, and the currently used biomarkers are not indicative of prognosis. The present study evaluated circulating tumor DNA (ctDNA) as a biomarker for prognosis prediction and disease monitoring in metastatic pancreatic adenocarcinoma (PAC).MethodsFrom 2017 to 2018, 40 patients with metastatic PAC were enrolled, and tumor tissue and blood samples were collected from 40 and 35 patients, respectively. CtDNA was sequenced by next-generation sequencing (NGS) with a 425-gene capture panel. The association of clinical characteristics, laboratory indicators, and dynamic ctDNA with patient outcomes was analyzed.ResultsMutations in KRAS (87.5%, N = 35) and TP53 (77.5%, N = 31) were most common in 40 tumor tissue. Patients’ ECOG score, CA19-9, CEA, neutrophil-lymphocyte ratio (NLR), platelet- lymphocyte ratio (PLR) levels and mutations in ≥ 3 driver genes were strongly correlated with patients’ overall survival (OS). Patients’ gender, ECOG score, CA19-9, and CEA levels were associated with progression-free survival (PFS) (P&lt;0.05). In 35 blood samples, univariate analysis showed a significant association between ECOG score, CA19-9, KRAS or CDKN2A mutation in ctDNA and OS and between CA19-9, CDKN2A or SMAD4 mutation in ctDNA and PFS. Cox hazard proportion model showed that patients’ CDKN2A mutation in ctDNA (HR=16.1, 95% CI=4.4-59.1, P&lt;0.001), ECOG score (HR=6.2, 95% CI=2.4-15.7, P&lt;0.001) and tumor location (HR=0.4, 95% CI=0.1-0.9, P=0.027) were significantly associated with OS. Patients’ CDKN2A mutation in ctDNA (HR=6.8, 95% CI=2.3-19.9, P=0.001), SMAD4 mutation in ctDNA (HR=3.0, 95% CI=1.1-7.9, P=0.031) and metastatic organ (HR=0.4, 95% CI=0.2-1.0, P=0.046) were significantly associated with PFS. Longitudinal changes in gene mutation allelic frequency (MAF) value were evaluated in 24 patients. Detection of progression disease (PD) by ctDNA was 0.9 months earlier than by radiological imaging (mean PFS: 4.6m vs 5.5m, P=0.004, paired t-test).ConclusionsThe ctDNA has the potential as a specific survival predictive marker for metastatic PAC patients. Longitudinal ctDNA tracking could potentially help identify disease progression and be a valuable complement for routine clinical markers and imaging.