Dataset Information

Combined utility of Ki-67 index and tumor grade to stratify patients with pancreatic ductal adenocarcinoma who underwent upfront surgery.

ABSTRACT:

Objective

To investigate the prognostic prediction of a new indicator, combined by tumor grade and Ki-67, in patients with resected pancreatic ductal adenocarcinoma (PDAC).

Methods

Data were retrospectively collected from consecutive patients who underwent primary resection of pancreas from December 2012 to December 2017. Tumor grade and Ki-67 were reviewed from routine pathological reports. G-Ki67 was classified as three categories as I (G1/2 and Ki-67 < 40%), II (G1/2 and Ki-67 ≥ 40%), and III(G3/4 and all Ki-67).

Results

Cox regression analyses revealed that tumor stage (II vs. I: hazard ratio (HR), 3.781; 95% confidence index (CI), 2.844-5.025; P < 0.001; III vs. I: HR, 7.476; 95% CI, 5.481-10.20; P < 0.001) and G-Ki67 (II vs. I: HR, 1.299; 95% CI, 1.038-1.624; P = 0.022; III vs. I: HR, 1.942; 95% CI, 1.477-2.554; P < 0.001) were independent prognostic factors in the developing cohort. The result was rectified in the validation cohort. In subgroups analysis, G-Ki67 (II vs. I: HR, 1.866 ; 95% CI, 1.045-3.334; P = 0.035; III vs. I: HR, 2.333 ; 95% CI, 1.156-4.705; P = 0.018) also had a high differentiation for survival prediction.

Conclusion

Our findings indicate that three-categories of G-Ki67 in resectable PDAC according to the routine pathological descriptions provided additional prognostic information complementary to the TNM staging system.

SUBMITTER: Li B

PROVIDER: S-EPMC10704770 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Combined utility of Ki-67 index and tumor grade to stratify patients with pancreatic ductal adenocarcinoma who underwent upfront surgery.

Li Bo B Yin Xiaoyi X Ding Xiuwen X Zhang Guoxiao G Jiang Hui H Chen Cuimin C Guo Shiwei S Jin Gang G

BMC surgery 20231208 1

<h4>Objective</h4>To investigate the prognostic prediction of a new indicator, combined by tumor grade and Ki-67, in patients with resected pancreatic ductal adenocarcinoma (PDAC).<h4>Methods</h4>Data were retrospectively collected from consecutive patients who underwent primary resection of pancreas from December 2012 to December 2017. Tumor grade and Ki-67 were reviewed from routine pathological reports. G-Ki67 was classified as three categories as I (G1/2 and Ki-67 < 40%), II (G1/2 and Ki-67 ...[more]

PMID: 38066512

Similar Datasets

Project description:ObjectiveTo develop and validate a model integrating dual-layer detector spectral computed tomography (DLCT) three-dimensional (3D) volume of interest (VOI)-based quantitative parameters and clinical features for predicting Ki-67 proliferation index (PI) in pancreatic ductal adenocarcinoma (PDAC).Materials and methodsA total of 162 patients with histopathologically confirmed PDAC who underwent DLCT examination were included and allocated to the training (114) and validation (48) sets. 3D VOI-iodine concentration (IC), 3D VOI-slope of the spectral attenuation curves, and 3D VOI-effective atomic number were obtained from the portal venous phase. The significant clinical features and DLCT quantitative parameters were identified through univariate analysis and multivariate logistic regression. The discrimination capability and clinical applicability of the clinical, DLCT, and DLCT-clinical models were quantified by the Receiver Operating Characteristic curve (ROC) and Decision Curve Analysis (DCA), respectively. The optimal model was then used to develop a nomogram, with the goodness-of-fit evaluated through the calibration curve.ResultsThe DLCT-clinical model demonstrated superior predictive capability and a satisfactory net benefit for Ki-67 PI in PDAC compared to the clinical and DLCT models. The DLCT-clinical model integrating 3D VOI-IC and CA125 showed area under the ROC curves of 0.939 (95% CI, 0.895-0.982) and 0.915 (95% CI, 0.834-0.996) in the training and validation sets, respectively. The nomogram derived from the DLCT-clinical model exhibited favorable calibration, as depicted by the calibration curve.ConclusionsThe proposed model based on DLCT 3D VOI-IC and CA125 is a non-invasive and effective preoperative prediction tool demonstrating favorable predictive performance for Ki-67 PI in PDAC.Critical relevance statementThe dual-layer detector spectral computed tomography-clinical model could help predict high Ki-67 PI in pancreatic ductal adenocarcinoma patients, which may help clinicians provide appropriate and individualized treatments.Key pointsDual-layer detector spectral CT (DLCT) could predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). The DLCT-clinical model improved the differential diagnosis of Ki-67. The nomogram showed satisfactory calibration and net benefit for discriminating Ki-67.

Dataset Information

Combined utility of Ki-67 index and tumor grade to stratify patients with pancreatic ductal adenocarcinoma who underwent upfront surgery.

Objective

Methods

Results

Conclusion

Publications

Combined utility of Ki-67 index and tumor grade to stratify patients with pancreatic ductal adenocarcinoma who underwent upfront surgery.

Similar Datasets

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