ChatGPT accurately performs genetic counseling for gynecologic cancers.

OBJECTIVE: Artificial Intelligence (AI) systems such as ChatGPT can take medical examinations and counsel patients regarding medical diagnosis. We aim to quantify the accuracy of the ChatGPT V3.4 in answering commonly asked questions pertaining to genetic testing and counseling for gynecologic cancers. METHODS: Forty questions were formulated in conjunction with gynecologic oncologists and adapted from professional society guidelines and ChatGPT version 3.5 was queried, the version that is readily available to the public. The two categories of questions were genetic counseling guidelines and questions pertaining to specific genetic disorders. The answers were scored by two attending Gynecologic Oncologists according to the following scale: 1) correct and comprehensive, 2) correct but not comprehensive, 3) some correct, some incorrect, and 4) completely incorrect. Scoring discrepancies were resolved by additional third reviewer. The proportion of responses earning each score were calculated overall and within each question category. RESULTS: ChatGPT provided correct and comprehensive answers to 33/40 (82.5%) questions, correct but not comprehensive answers to 6/40 (15%) questions, partially incorrect answers to 1/40 (2.5%) questions, and completely incorrect answers to 0/40 (0%) questions. The genetic counseling category of questions had the highest proportion of answers that were both correct and comprehensive with ChatGPT answering all 20/20 questions with 100% accuracy and were comprehensive in responses. ChatGPT performed equally in the specific genetic disorders category, with 88.2% (15/17) and 66.6% (2/3) correct and comprehensive answers to questions pertaining to hereditary breast and ovarian cancer and Lynch syndrome questions respectively. CONCLUSION: ChatGPT accurately answers questions about genetic syndromes, genetic testing, and counseling in majority of the studied questions. These data suggest this powerful tool can be utilized as a patient resource for genetic counseling questions, though more data input from gynecologic oncologists would be needed to educate patients on genetic syndromes.

Let's chat about cervical cancer: Assessing the accuracy of ChatGPT responses to cervical cancer questions.

OBJECTIVE: To quantify the accuracy of ChatGPT in answering commonly asked questions pertaining to cervical cancer prevention, diagnosis, treatment, and survivorship/quality-of-life (QOL). METHODS: ChatGPT was queried with 64 questions adapted from professional society websites and the authors' clinical experiences. The answers were scored by two attending Gynecologic Oncologists according to the following scale: 1) correct and comprehensive, 2) correct but not comprehensive, 3) some correct, some incorrect, and 4) completely incorrect. Scoring discrepancies were resolved by additional reviewers as needed. The proportion of responses earning each score were calculated overall and within each question category. RESULTS: ChatGPT provided correct and comprehensive answers to 34 (53.1%) questions, correct but not comprehensive answers to 19 (29.7%) questions, partially incorrect answers to 10 (15.6%) questions, and completely incorrect answers to 1 (1.6%) question. Prevention and survivorship/QOL had the highest proportion of "correct" scores (scores of 1 or 2) at 22/24 (91.7%) and 15/16 (93.8%), respectively. ChatGPT performed less well in the treatment category, with 15/21 (71.4%) correct scores. It performed the worst in the diagnosis category with only 1/3 (33.3%) correct scores. CONCLUSION: ChatGPT accurately answers questions about cervical cancer prevention, survivorship, and QOL. It performs less accurately for cervical cancer diagnosis and treatment. Further development of this immensely popular large language model should include physician input before it can be utilized as a tool for Gynecologists or recommended as a patient resource for information on cervical cancer diagnosis and treatment.

Utilization and outcomes of sentinel lymph node biopsy in patients with early stage vulvar cancer.

OBJECTIVE: A retrospective cohort study comparing survival and perioperative outcomes of patients with early vulvar cancer who underwent sentinel lymph node biopsy versus standard lymphadenectomy METHODS: Patients diagnosed between January 2012 and December 2015 with vulvar squamous cell carcinoma of less than 4 cm in size, with invasion of at least 1 mm, who underwent sentinel lymph node biopsy, lymphadenectomy, or both were identified from the National Cancer Database. Overall survival was evaluated following generation of Kaplan-Meier curves and compared with the log-rank test for patients who had at least 1 month of follow-up. A Cox model was constructed to control for confounders. RESULTS: A total of 1583 patients were identified; 304 patients (19.2%) underwent sentinel lymph node biopsy alone. Sentinel lymph node biopsy utilization increased 13.9% between 2012 and 2015. Patients who underwent sentinel node biopsy alone were less likely to have comorbidities compared with those undergoing lymphadenectomy only or sentinel node biopsy with lymphadenectomy (25.3% vs 32.9% vs 31.9%, p=0.042), had smaller tumors (median 1.6 vs 2.0 vs 2.0 cm, p<0.001), and were less likely to have positive lymph nodes (11% vs 19.6% vs 28.1%, p<0.001). There was no difference in 3 year overall survival between the three groups (86.3% vs 82.1% vs 77.9%, p=0.26). After controlling for age, race, insurance, comorbidities, lymph node metastases, and tumor size, sentinel lymph node biopsy alone was not associated with worse overall survival compared with lymphadenectomy (HR 0.86, 95% CI 0.57 to 1.32). The sentinel node only group had shorter inpatient stays compared with lymphadenectomy only (median 1 vs 2 days, p<0.001) and a lower rate of unplanned readmission (1.7% vs 5.0%, p=0.010). CONCLUSIONS: The utilization of sentinel lymph node biopsy is increasing in the management of vulvar cancer and is associated with superior perioperative outcomes without impacting overall survival.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of ß-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

Predictive value of 5-Factor modified frailty index in Oncologic and benign hysterectomies.

Background: The 5-factor modified frailty index (mFI-5) has been validated against the original 11-factor modified frailty index in gynecologic surgery, however its utility has not been evaluated between benign versus gynecologic oncology patient populations. Objective: To evaluate the predictive value of the mFI-5 in identifying women at increased risk for major postoperative complications, readmission, or death within 30 days of hysterectomy for benign and oncologic indications. Methods: Patients who underwent hysterectomy between 2015 and 2017 were identified from the NSQIP database and stratified into benign or malignant indications. Demographic and mFI-5 variables were extracted. The mFI-5 was calculated by dividing the sum of all affirmative variables by the total number of input variables in the database. Logistic regression modeling was performed adjusting for confounders. C-statistic with 95% CI was obtained post-regression. Results: 80,293 hysterectomies (59,078 benign and 21,215 oncologic) were identified. The benign group was more likely to have an mFI-5 score of 0 (70 % vs 50 %, p = 0.001) and had shorter operative times (p = 0.001). In the benign group, mFI-5 was a strong predictor of mortality (c = 0.819, CI 0.704-0.933). Within the oncology group, the mFI-5 was a strong predictor of mortality (c = 0.801, CI 0.750-0.851), particularly for uterine and cervical cancers. It was moderately predictive of readmission (c = 0.671, CI 0.656-0.686) and strongly predictive of Clavien-Dindo class III and IV complications (c = 0.732, CI 0.713-0.750). Conclusion: The mFI-5 is a strong predictor of 30-day mortality and serious postoperative complications. These findings have the potential to improve identification of high-risk patients in the preoperative setting.

Improving obstetric hemorrhage morbidity by a checklist-based management protocol; a quality improvement initiative.

OBJECTIVE: Postpartum hemorrhage is a leading cause of maternal morbidity and mortality worldwide. Institutions are encouraged to have a standardized approach to the management of obstetric hemorrhage. The purpose of this quality improvement project was to investigate postpartum hemorrhage associated morbidity before and after implementing an obstetric hemorrhage checklist-based protocol. STUDY DESIGN: In 2015, a resident-driven initiative for obstetric hemorrhage was initiated at a single institution using a checklist-based protocol for postpartum hemorrhage. The project included development of the obstetric hemorrhage checklist by a multidisciplinary team and implementation using low cost education and training strategies. Following implementation, a pre-and post-protocol retrospective analysis was performed measuring maternal morbidity surrogates and protocol compliance. During the 18 month study period, 422 women were identified for review and 147 met criteria in the pre-protocol group and 150 met criteria in the post-protocol group. RESULTS: There was a significant decrease in severe postpartum hemorrhage rates in the post-protocol group (p = 0.04) and all other surrogates for maternal morbidity decreased in the post-protocol group. Protocol compliance was 62.2% and compliance with screening using an assessment of hemorrhage risk was 75.7%. CONCLUSION: The implementation of a checklist-based management protocol for postpartum hemorrhage has shown a promising trend in improving maternal morbidity, screening, early diagnosis, and healthcare delivery for obstetric hemorrhage at our institution and has been approved for larger scale implementation within our health system.