Prediction model for estimating the survival benefit of adjuvant radiotherapy for gallbladder cancer
ABSTRACT The benefit of adjuvant radiotherapy (RT) for gallbladder cancer remains controversial because most published data are from small, single-institution studies. The purpose of this study was to construct a survival prediction model to enable individualized predictions of the net survival benefit of adjuvant RT for gallbladder cancer patients based on specific tumor and patient characteristics.
A multivariate Cox proportional hazards model was constructed using data from 4,180 patients with resected gallbladder cancer diagnosed from 1988 to 2003 from the Surveillance, Epidemiology, and End Results database. Patient and tumor characteristics were included as covariates and assessed for association with overall survival (OS) with and without adjuvant RT. The model was internally validated for discrimination and calibration using bootstrap resampling.
On multivariate regression analysis, the model showed that age, sex, papillary histology, stage, and adjuvant RT were significant predictors of OS. The survival prediction model demonstrated good calibration and discrimination, with a bootstrap-corrected concordance index of 0.71. The model predicts that adjuvant RT provides a survival benefit in node-positive or >or= T2 disease. A nomogram and a browser-based software tool were built from the model that can calculate individualized estimates of predicted net survival gain attributable to adjuvant RT, given specific input parameters.
In the absence of large, prospective, randomized, clinical trial data, a regression model can be used to make individualized predictions of the expected survival improvement from the addition of adjuvant RT after gallbladder cancer resection.
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ABSTRACT: Biliary tract cancers are a rare subgroup of malignancies that include gall bladder carcinoma and cholangiocarcinoma. They generally carry a poor prognosis based on the advanced nature of disease at presentation and overall treatment refractoriness. Surgical resection remains the optimal treatment for long-term survival, with consideration of neoadjuvant or adjuvant therapies. In this review, we summarize the role of adjuvant treatments including radiation therapy, chemotherapy, and concurrent chemoradiation with the existing clinical evidence for each treatment decision. Given the rarity of these tumors, the evidence provided is based largely on retrospective studies, Surveillance, Epidemiological, and End Results (SEER) database inquiries, single- or multi-institutional prospective studies, and a meta-analysis of adjuvant therapy studies. Currently, there is no adjuvant therapy that has been agreed upon as a standard of care. Results from prospective, multi-institutional phase II and III trials are awaited, along with advances in molecular targeted therapies and radiation techniques, which will better define treatment standards and improve outcomes in this group of diseases.Seminars in radiation oncology 04/2014; 24(2):94–104. DOI:10.1016/j.semradonc.2014.01.001 · 3.77 Impact Factor
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ABSTRACT: The benefits of adjuvant cytokine-induced killer (CIK) cell immunotherapy for hepatocellular carcinoma (HCC) remain mixed among patients. Here, we constructed a prognostic nomogram to enable individualized predictions of survival benefit of adjuvant CIK cell treatment for HCC patients. Survival analysis showed that the median overall survival (OS) and progression-free survival (PFS) for patients in the hepatectomy/CIK combination group were 41 and 16 months, respectively, compared to 28 and 12 months for patients in the hepatectomy alone group (control). Based on multivariate analysis of the entire cohort, independent factors for OS were tumor size, tumor capsule, pathological grades, total bilirubin, albumin, prothrombin time, alpha-fetoprotein, and tumor number, which were incorporated into the nomogram. The survival prediction model performed well, as assessed by the c-index and calibration curve. Internal validation revealed a c-index of 0.698, which was significantly greater than the c-index value of the TNM (tumor-node-metastasis) staging systems of 0.634. The calibration curves fitted well. In conclusions, our developed nomogram resulted in more accurate individualized predictions of the survival benefit from adjuvant CIK cell treatment after hepatectomy. The model may provide valuable information to aid in the decision making regarding the application of adjuvant CIK cell immunotherapy.Scientific Reports 03/2015; 5:9202. DOI:10.1038/srep09202 · 5.08 Impact Factor