Nomogram to predict perioperative blood transfusion for hepatopancreaticobiliary and colorectal surgery

Kim, Y.; Bagante, Fabio; Gani, Faiz; Ejaz, Aslam; Xu, Li; Wasey, Jack O.; Johnson, Daniel J.; Frank, Steven M.; Pawlik, Timothy M.

doi:10.1002/bjs.10164

Cited by 18 publications

(20 citation statements)

References 49 publications

(83 reference statements)

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“…Regarding preoperative assessment of the risk for transfusion, guidelines recommended reviewing available laboratory test results including hemoglobin and coagulation pro les (i.e., INR, platelet), all of which were assessed in this study. As expected, preoperative hemoglobin level was the most powerful predictor in this predictive model, which was similar to other predictive models for hepatopancreaticobiliary surgery [16] and hepatectomy [17]. In this study, using preoperative hemoglobin level greater than or equal to 120 g/L as a reference, hemoglobin level less than 80 g/l contributed 100 points to the nomogram.…”

Section: Discussionsupporting

confidence: 85%

“…In addition, accurately predicting the risk of perioperative transfusion could be of bene t to plan necessary procedure including central venous access, invasive hemodynamic monitoring. Recently, various predictive models have been developed to predict the likelihood of blood transfusion for different surgical types, such as spinal surgery [14], cardiac surgery [15], hepatopancreaticobiliary and colorectal surgery [16]. To date, however, a predictive model regarding the risk of perioperative blood transfusion for gastrectomy has not been proposed.…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of a nomogram to predict perioperative blood transfusion for gastric cancer surgery

Huang

Han

Xia

et al. 2020

Preprint

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Background This study aimed to construct and validate a nomogram composed of preoperative variables to predict perioperative blood transfusion for gastric cancer surgery. Methods 600 gastric cancer patients undergoing gastrectomy between January 2010 and December 2015 were selected as primary cohort. 399 patients from January 2016 to June 2019 were collected as validation cohort. In the primary cohort, univariate and multivariate analyses were performed to identify independent risk factors for blood transfusion. Using Akaike information criterion, selected variables were incorporated to construct a nomogram. Validations of the nomogram were performed in the primary and validation cohort. Discrimination of the nomogram was assessed by the concordance index (C-index) and calibration of the nomogram was assessed by calibration curve and Hosmer–Lemeshow goodness-of-fit test. Results The following independent risk factors for transfusion were identified: Charlson comorbidity index score over 3 (odds ratio (OR) 2.15), tumor location (diffuse vs upper: OR 1.50), pTNM stage (III vs I: OR 3.17), type of gastrectomy (subtotal vs total gastrectomy: OR 0.58), extragastric organ resection (OR 2.03) and preoperative hemoglobin less than 80 g/l (vs over 120 g/l: OR 66.03). C-index was 0.863 and 0.901 in the primary and validation cohort, respectively, indicating good discrimination of the nomogram. Both calibration curves and Hosmer–Lemeshow goodness-of-fit tests (P-value 0.716 and 0.935) demonstrated high agreement between prediction and actual outcome. Conclusion A nomogram composed of preoperative variables to predict blood transfusion for gastric cancer surgery was developed and validated. This nomogram could be used to improve utilization of packed red blood cells.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram to predict perioperative blood transfusion for gastric cancer surgery

Huang

Han

Xia

et al. 2020

Preprint

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“…More recently, there has been an increased focus on using specific patient‐ and tumor‐level characteristics to provide individualized survival estimates. To this end, various groups have advocated for nomograms as a means to integrate individual‐level variables into a statistical model to predict outcomes . The applicability and clinical utility of nomograms are frequently limited, however, due to their cumbersome nature, as well as the inability to easily and readily use nomograms in a simple, real‐world clinical setting.…”

Section: Introductionmentioning

confidence: 99%

A novel online prognostic tool to predict long‐term survival after liver resection for intrahepatic cholangiocarcinoma: The “metro‐ticket” paradigm

Sahara

Tsilimigras

Mehta

et al. 2019

Journal of Surgical Oncology

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Background The aim of the current study was to develop an online calculator to predict survival after liver resection for intrahepatic cholangiocarcinoma (ICC) based on the “metro‐ticket” paradigm. Methods Between 1990 and 2016, patients who underwent liver resection for ICC were identified in an international multi‐institutional database. The final multivariable model of survival was used to develop an online prognostic calculator of survival. Results Among 643 patients, actual 5‐year overall survival (OS) after resection for ICC was 42.7%. On multivariable analysis, CA19‐9 > 200 (hazard ratio (HR), 2.62; 95% CI, 2.01‐3.42), sum of the number and largest tumor size >7 (HR, 1.88; 95% CI, 1.46‐2.42), N1 disease (HR, 2.87; 95% CI, 1.98‐4.16), R1 resection (HR, 1.72; 95% CI, 1.21‐2.46), poor/undifferentiated tumor grade (HR, 1.74; 95% CI, 1.25‐2.44), major vascular invasion (HR, 1.47; 95% CI, 1.03‐2.10), and adjuvant chemotherapy (HR, 0.64; 95% CI, 0.45‐0.89) were significantly associated with survival and were included in the online calculator. The predictive accuracy of the model was good to very good as the C‐statistics to predict 5‐year OS was 0.696 in the training dataset and 0.672 with bootstrapping resamples (n = 5000) in the test dataset. Conclusion A novel, online calculator was developed to estimate the 5‐year survival probability for patients undergoing resection for ICC. This tool could help provide useful information to guide treatment decision‐making and inform conversations about prognosis.

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“…Potential reasons include the complexity of the underlying cause, and lack of standardization of practices. One recent study by Kim et al developed a nomogram to predict perioperative blood transfusion after hepatopancreaticobiliary and CRS using traditional statistical methods and achieved an area under the operating curve of 0.756 7 .…”

Section: Introductionmentioning

confidence: 99%

Postoperative bleeding risk prediction for patients undergoing colorectal surgery

Chen¹,

Afzal²,

Sohn³

et al. 2018

Surgery

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Nomogram to predict perioperative blood transfusion for hepatopancreaticobiliary and colorectal surgery

Abstract: The nomogram predicted blood transfusion in major HPB and colorectal surgery.

Cited by 18 publications

References 49 publications

Development and validation of a nomogram to predict perioperative blood transfusion for gastric cancer surgery

Development and validation of a nomogram to predict perioperative blood transfusion for gastric cancer surgery

A novel online prognostic tool to predict long‐term survival after liver resection for intrahepatic cholangiocarcinoma: The “metro‐ticket” paradigm

Postoperative bleeding risk prediction for patients undergoing colorectal surgery

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