Dataset Information

Predictive modeling for determination of microscopic residual disease at primary cytoreduction: An NRG Oncology/Gynecologic Oncology Group 182 Study.

ABSTRACT: OBJECTIVE:Microscopic residual disease following complete cytoreduction (R0) is associated with a significant survival benefit for patients with advanced epithelial ovarian cancer (EOC). Our objective was to develop a prediction model for R0 to support surgeons in their clinical care decisions. METHODS:Demographic, pathologic, surgical, and CA125 data were collected from GOG 182 records. Patients enrolled prior to September 1, 2003 were used for the training model while those enrolled after constituted the validation data set. Univariate analysis was performed to identify significant predictors of R0 and these variables were subsequently analyzed using multivariable regression. The regression model was reduced using backward selection and predictive accuracy was quantified using area under the receiver operating characteristic area under the curve (AUC) in both the training and the validation data sets. RESULTS:Of the 3882 patients enrolled in GOG 182, 1480 had complete clinical data available for the analysis. The training data set consisted of 1007 patients (234 with R0) while the validation set was comprised of 473 patients (122 with R0). The reduced multivariable regression model demonstrated several variables predictive of R0 at cytoreduction: Disease Score (DS) (p<0.001), stage (p=0.009), CA125 (p<0.001), ascites (p<0.001), and stage-age interaction (p=0.01). Applying the prediction model to the validation data resulted in an AUC of 0.73 (0.67 to 0.78, 95% CI). Inclusion of DS enhanced the model performance to an AUC of 0.83 (0.79 to 0.88, 95% CI). CONCLUSIONS:We developed and validated a prediction model for R0 that offers improved performance over previously reported models for prediction of residual disease. The performance of the prediction model suggests additional factors (i.e. imaging, molecular profiling, etc.) should be explored in the future for a more clinically actionable tool.

SUBMITTER: Horowitz NS

PROVIDER: S-EPMC5962447 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Predictive modeling for determination of microscopic residual disease at primary cytoreduction: An NRG Oncology/Gynecologic Oncology Group 182 Study.

Horowitz Neil S NS Larry Maxwell G G Miller Austin A Hamilton Chad A CA Rungruang Bunja B Rodriguez Noah N Richard Scott D SD Krivak Thomas C TC Fowler Jeffrey M JM Mutch David G DG Van Le Linda L Lee Roger B RB Argenta Peter P Bender David D Tewari Krishnansu S KS Gershenson David D Java James J JJ Bookman Michael A MA

Gynecologic oncology 20171123 1

<h4>Objective</h4>Microscopic residual disease following complete cytoreduction (R0) is associated with a significant survival benefit for patients with advanced epithelial ovarian cancer (EOC). Our objective was to develop a prediction model for R0 to support surgeons in their clinical care decisions.<h4>Methods</h4>Demographic, pathologic, surgical, and CA125 data were collected from GOG 182 records. Patients enrolled prior to September 1, 2003 were used for the training model while those enro ...[more]

PMID: 29174555

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Project description:BackgroundBlack women with endometrial cancer are more likely to die of their disease compared with white women with endometrial cancer. These survival disparities persist even when disproportionately worse tumor characteristics among black women are accounted. Receipt of less complete adjuvant treatment among black patients with endometrial cancer could contribute to this disparity.ObjectiveWe assessed the hypothesis that black women with endometrial cancer are less likely than their white counterparts to receive adjuvant treatment within subgroups defined by tumor characteristics in the NRG Oncology/Gynecology Oncology Group 210 Study.Study designOur analysis included 615 black and 4283 white women with endometrial cancer who underwent hysterectomy. Women completed a questionnaire that assessed race and endometrial cancer risk factors. Tumor characteristics were available from pathology reports and central review. We categorized women as low-, intermediate-, or high-risk based on the European Society for Medical Oncology definition. Adjuvant treatment was documented during postoperative visits and was categorized as no adjuvant treatment (54.3%), radiotherapy only (16.5%), chemotherapy only (15.2%), and radiotherapy plus chemotherapy (14.0%). We used polytomous logistic regression to estimate odds ratios and 95% confidence intervals for multivariable-adjusted associations between race and adjuvant treatment in the overall study population and stratified by tumor subtype, stage, or European Society for Medical Oncology risk category.ResultsOverall, black women were more likely to have received chemotherapy only (odds ratio, 1.40; 95% confidence interval, 1.04-1.86) or radiotherapy plus chemotherapy (odds ratio, 2.01; 95% confidence interval, 1.54-2.62) compared with white women in multivariable-adjusted models. No racial difference in the receipt of radiotherapy only was observed. In tumor subtype-stratified models, black women had higher odds of receiving radiotherapy plus chemotherapy than white women when diagnosed with low-grade endometrioid (odds ratio, 2.04; 95% confidence interval, 1.06-3.93) or serous tumors (odds ratio, 1.81; 95% confidence interval, 1.07-3.08). Race was not associated with adjuvant treatment among women who had been diagnosed with other tumor subtypes. In stage-stratified models, we observed no racial differences in the receipt of adjuvant treatment. In models that were stratified by European Society for Medical Oncology risk group, black women with high-risk cancer were more likely to receive radiotherapy plus chemotherapy compared with white women (odds ratio, 1.41; 95% confidence interval, 1.03-1.94).ConclusionContrary to our hypothesis, we observed higher odds of specific adjuvant treatment regimens among black women as compared with white women within specific subgroups of endometrial cancer characteristics.

Project description:Stage is a critical determinant of treatment among endometrial carcinoma patients; understanding patterns of tumor spread may suggest approaches to improve staging. Specifically, the importance of exfoliation of endometrial carcinoma cells through the fallopian tubes into the peritoneum is ill defined. We assessed the hypothesis that tubal ligation (TL), which should impede transtubal passage of cells, is associated with lower endometrial carcinoma stage at presentation and, consequently, lower mortality.The NRG Oncology/Gynecologic Oncology Group (GOG) 210 Trial included 4489 endometrial carcinoma patients who completed a risk factor questionnaire that included TL history. Pathology data were derived from clinical reports and central review. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between TL with stage and peritoneal metastasis, overall and by tumor subtype. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals for TL and mortality. All statistical tests were two-sided.Compared with stage I, TL was inversely associated with stage III (OR = 0.63, 95% CI = 0.52 to 0.78) and stage IV carcinomas (OR = 0.14, 95% CI = 0.08 to 0.24) overall and among individual tumor subtypes. TL was inversely related to peritoneal metastasis overall (OR = 0.39, 95% CI = 0.22 to 0.68) and among serous carcinomas (OR = 0.28, 95% CI = 0.11 to 0.68). In multivariable models unadjusted for stage, TL was associated with lower endometrial carcinoma-specific mortality (HR = 0.74, 95% CI = 0.61 to 0.91); however, adjustment for stage eliminated the survival advantage. Similar relationships with all-cause mortality were observed.TL is associated with lower stage and mortality among women with aggressive endometrial carcinomas, suggesting transtubal spread is clinically important. Future studies should evaluate whether detection of intraluminal tumor cells is prognostically relevant.

Dataset Information

Predictive modeling for determination of microscopic residual disease at primary cytoreduction: An NRG Oncology/Gynecologic Oncology Group 182 Study.

Publications

Predictive modeling for determination of microscopic residual disease at primary cytoreduction: An NRG Oncology/Gynecologic Oncology Group 182 Study.

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