Surgical Predictive Model for Breast Cancer Patients Assessing Acute Postoperative Complications: The Breast Cancer Surgery Risk Calculator.
Surgical Predictive Model for Breast Cancer Patients Assessing Acute Postoperative Complications: The Breast Cancer Surgery Risk Calculator.
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用于评估乳腺癌患者术后急性并发症的手术预测模型：乳腺癌手术风险计算器
DOI：
10.1245/s10434-021-09710-8
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发表时间：
2021-09
影响因子：
3.7
通讯作者：
Chatterjee A
中科院分区：
文献类型：
--
作者：
Jonczyk MM;Fisher CS;Babbitt R;Paulus JK;Freund KM;Czerniecki B;Margenthaler JA;Losken A;Chatterjee A
预后工具，如风险计算器，改善病人-医生知情的决策过程。在术前评估手术并发症风险时，这些工具仅限于乳腺癌患者。在这里，我们旨在评估与乳腺癌患者急性术后并发症相关的预测因素，然后开发一个预测模型，使用患者风险因素计算并发症概率。我们使用2005-2017年的NSQIP数据库进行了回顾性队列研究。诊断为导管原位癌或浸润性乳腺癌的女性接受保乳或乳房切除术，包括在这个预测建模方案。使用逻辑回归方法建立四个模型来预测以下复合结局：总体、感染、血液学和内脏并发症。内部/外部验证期间的模型性能、准确度和校准测量分别包括曲线下面积、brier评分和Hosmer-Lemeshow统计量。共有163，613名女性符合入选标准。每个模型的曲线下面积为：总体0.70，感染0.67，血液学0.84和内部器官0.74。Brier评分均在0.04-0.003之间。使用Hosmer-Lemeshow统计量的模型校准发现所有p值>0.05。使用模型系数，可以在基于网络的乳腺癌手术风险计算器（BCSRc）平台上计算个体化风险; www.breastcalc.org。我们开发了一个内部和外部验证的风险计算器，用于估计乳腺癌患者每次手术干预后急性并发症的独特风险。术前使用BCSRc可能有助于对并发症风险增加的患者进行分层，并提高决策过程中的预期。
Prognostic tools, such as risk calculators, improve the patient-physician informed decision making process. These tools are limited for breast cancer patients when assessing surgical complication risk pre-operatively. Here we aimed to assess predictors associated with acute postoperative complications for breast cancer patients and then develop a predictive model that calculates a complication probability using patient risk factors. We performed a retrospective cohort study using the NSQIP database from 2005–2017. Women diagnosed with ductal carcinoma in situ or invasive breast cancer who underwent either breast conservation or mastectomy procedures were included in this predictive modeling scheme. Four models were built using logistic regression methods to predict the following composite outcomes: overall, infectious, hematologic, and internal organ complications. Model performance, accuracy and calibration measures during internal/external validation included area under the curve, the brier score and Hosmer-Lemeshow statistic; respectively. A total of 163,613 women met inclusion criteria. Area under the curve for each model was: Overall 0.70, Infectious 0.67, Hematologic 0.84, and Internal Organ 0.74. Brier scores were all between 0.04–0.003. Model calibration using the Hosmer- Lemeshow statistic found all p-values >0.05. Using model coefficients, individualized risk can be calculated on the web-based breast cancer surgical risk calculator (BCSRc) platform; www.breastcalc.org. We developed an internally and externally-validated risk calculator that estimates a breast cancer patient’s unique risk of acute complications following each surgical intervention. Preoperative use of the BCSRc can potentially help stratify patients with an increased complication risk and improve expectations during the decision making process.
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DOI：
10.1097/gox.0000000000000351
发表时间：
2015-05-01
影响因子：
1.5
作者：
Kim, John Y. S.;Mlodinow, Alexei S.;Gutowski, Karol A.
通讯作者：
Gutowski, Karol A.
影响因子：
3.6
作者：
Albornoz, Claudia R.;Bach, Peter B.;Matros, Evan
通讯作者：
Matros, Evan
影响因子：
3
作者：
Basta, Marten N.;Bauder, Andrew R.;Fischer, John P.
通讯作者：
Fischer, John P.
影响因子：
5.2
作者：
Jonczyk, Michael M.;Jean, Jolie;Chatterjee, Abhishek
通讯作者：
Chatterjee, Abhishek
影响因子：
51.1
作者：
Krag, David N.;Anderson, Stewart J.;Julian, Thomas B.;Brown, Ann M.;Harlow, Seth P.;Costantino, Joseph P.;Ashikaga, Takamaru;Weaver, Donald L.;Mamounas, Eleftherios P.;Jalovec, Lynne M.;Frazier, Thomas G.;Noyes, R. Dirk;Robidoux, Andre;Scarth, Hugh M. C.;Wolmark, Norman
通讯作者：
Wolmark, Norman