Prediction of overall survival for metastatic pancreatic cancer: Development and validation of a prognostic nomogram with data from open clinical trial and real‐world study

Abstract

It is necessary to develop prognostic tools of metastatic pancreatic cancer (MPC) for optimizing therapeutic strategies. Thus, we tried to develop and validate a prognostic nomogram of MPC. Data from 3 clinical trials (NCT00844649, NCT01124786, and NCT00574275) and 133 Chinese MPC patients were used for analysis. The former 2 trials were taken as the training cohort while NCT00574275 was used as the validation cohort. In addition, 133 MPC patients treated in China were taken as the testing cohort. Cox regression model was used to investigate prognostic factors in the training cohort. With these factors, we established a nomogram and verified it by Harrell's concordance index (C‐index) and calibration plots. Furthermore, the nomogram was externally validated in the validation cohort and testing cohort. In the training cohort (n = 445), performance status, liver metastasis, Carbohydrate antigen 19‐9 (CA19‐9) log‐value, absolute neutrophil count (ANC), and albumin were independent prognostic factors for overall survival (OS). A nomogram was established with these factors to predict OS and survival probabilities. The nomogram showed an acceptable discrimination ability (C‐index: .683) and good calibration, and was further externally validated in the validation cohort (n = 273, C‐index: .699) and testing cohort (n = 133, C‐index: .653).The nomogram total points (NTP) had the potential to stratify patients into 3‐risk groups with median OS of 11.7, 7.0 and 3.7 months (P < .001), respectively. In conclusion, the prognostic nomogram with NTP can predict OS for patients with MPC with considerable accuracy.

Prognostic and predictive factors in pancreatic cancer

“…Recently Hang et al [120] developed and validated a prognostic nomogram considering data from the comparative arm of three trials where metastatic pancreatic patients received gemcitabine monotherapy. They inserted five independent prognostic elements: CA19-9; albumin; absolute neutrophil count (ANC), PS and liver metastasis.…”

Validation and application of a prognostic model for patients with advanced pancreatic cancer receiving palliative chemotherapy

“…In line with the GS model, the current study helped identify performance status, tumor stage, albumin, and NLR as independent prognostic factors that predict survival outcome. Several prognostic models have been developed for survival prediction among APC patients receiving first‐line palliative chemotherapy . Apart from patient factors (age, sex, performance status, weight loss), laboratory variables (albumin, white cell count, NLR, tumor markers) and tumor characteristics (stage, tumor size, metastatic organ, ascites) have all been reported to be independent prognosticators in different prognostic models .…”

“…Table summarizes and compares 13 published prognostic models for the prediction of the survival outcome of PC patients receiving palliative chemotherapy from a literature review . Only one of the models was designed prospectively ; the others were retrospective studies.…”

“…Only one of the models was designed prospectively ; the others were retrospective studies. Of the 13 prognostic models, some were used for the prediction of survival outcome specifically for gemcitabine‐based treatment, while the other models consisted a broad spectrum of chemotherapeutic regimens . The performance reflected by C‐index ranged from 0.66 to 0.80 among these prognostic models.…”

“…The performance reflected by C‐index ranged from 0.66 to 0.80 among these prognostic models. Only five models were validated by application to a different cohort . Because the GS model is easily applied and had good performance in term of C‐index value in the original and the current cohort, we believe this model to be widely applicable by clinicians to predict survival outcome in APC patients receiving first‐line palliative chemotherapy.…”