Faculty Bibliography

PURPOSE OF REVIEW/OBJECTIVE:The Cancer Genome Atlas identified four distinct molecular subtypes of endometrial cancer (EC): POLE mutated, mismatch repair deficient (dMMR), copy number low, and copy number high. The goal of this review is to summarize the profound clinical implications of molecular subtyping, particularly in guiding treatment decisions for dMMR and microsatellite instability high (MSI-H) EC. RECENT FINDINGS/RESULTS:Clinical trials have demonstrated the remarkable efficacy of immunotherapy in dMMR/MSI-H EC tumors. Trials including GARNET, KEYNOTE-158, NRG GY-018, and RUBY have shown significant improvements in clinical outcomes for patients with advanced and recurrent disease, leading to FDA approvals for immunotherapy in both frontline and recurrent EC treatment settings.Building on these successes, recent studies, including DUO-E, are exploring combination therapies to enhance the efficacy of immunotherapy in EC. Simultaneously, trials including NRG GY-020, are investigating the potential benefits of immunotherapy in early-stage disease. SUMMARY/CONCLUSIONS:Immunotherapy therapy has revolutionized the treatment of endometrial cancer in both upfront and recurrent settings, with molecular subtyping identifying patients most likely to benefit, especially those with dMMR/MSI-H tumors.

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/CONCLUSIONS: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.

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/CONCLUSIONS: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.

Radiation Recall encompasses an array of inflammatory reactions, most commonly dermatitis, that occurs in response to a systemic medication with distribution in a previously irradiated field. While historically cytotoxic chemotherapy was a major culprit, this case report describes radiation recall dermatitis in response to pembrolizumab and lenvatinib in a 62-year old female with ongoing advanced endometrial cancer and history of breast cancer. Discontinuation of lenvatinib alone lead to complete resolution of the dermatitis, and she ultimately resumed her previous lenvatinib dose without recurrent symptoms. This case represents an important possible adverse effect of a commonly used targeted therapy, particularly in a population likely to have a history of prior radiation exposure.

Radiation Recall encompasses an array of inflammatory reactions, most commonly dermatitis, that occurs in response to a systemic medication with distribution in a previously irradiated field. While historically cytotoxic chemotherapy was a major culprit, this case report describes radiation recall dermatitis in response to pembrolizumab and lenvatinib in a 62-year old female with ongoing advanced endometrial cancer and history of breast cancer. Discontinuation of lenvatinib alone lead to complete resolution of the dermatitis, and she ultimately resumed her previous lenvatinib dose without recurrent symptoms. This case represents an important possible adverse effect of a commonly used targeted therapy, particularly in a population likely to have a history of prior radiation exposure.

OBJECTIVE:To evaluate utilization of sentinel lymph node biopsy (SLNB) for early-stage vulvar cancer at minority-serving hospitals and low-volume facilities. METHODS:Between 2012-2018, individuals with T1b vulvar squamous cell carcinoma were identified using the National Cancer Database. Patient, facility, and disease characteristics were compared between patients undergoing SLNB or inguinofemoral lymph node dissection (IFLD). Multivariable logistic regression, adjusted for patient, facility, and disease characteristics, was used to evaluate factors associated with SLNB. Kaplan-Meier survival analysis using log rank test and Cox regression was performed. RESULTS:Of the 3,532 patients, 2,406 (68.1%) underwent lymph node evaluation, with 1,704 (48.2%) undergoing IFLD and 702 (19.8%) SLNB. In a multivariable analysis, treatment at minority-serving hospitals (OR 0.39, 95% CI 0.19-0.78) and low-volume hospitals (OR 0.44, 95% CI 0.28-0.70) were associated with significantly lower odds of undergoing SLNB compared to receiving care at non-minority-serving and high-volume hospitals, respectively. While SLNB utilization increased over time for the entire cohort and stratified subgroups, use of the procedure did not increase at minority-serving hospitals. After controlling for patient and tumor characteristics, SLNB was not associated with worse OS compared to IFLD in patients with positive (HR 1.02, 95% CI 0.63-1.66) or negative (HR 0.92, 95% CI 0.70-1.21) nodal pathology. CONCLUSIONS:For patients with early-stage vulvar cancer, treatment at minority-serving or low-volume hospitals was associated with significantly decreased odds of undergoing SLNB. Future efforts should be concentrated toward ensuring that all patients have access to advanced surgical techniques regardless of where they receive their care.

OBJECTIVE:To describe the use of National Comprehensive Cancer Network guideline-concordant inguinofemoral lymph node (LN) evaluation in individuals with early-stage vulvar cancer. METHODS:This retrospective cohort study identified patients with T1b and T2 vulvar squamous cell carcinoma diagnosed between 2012 and 2018 using the National Cancer Database. Factors associated with LN evaluation were examined using logistic regression analyses, adjusting for patient, disease, and facility-level characteristics. Kaplan-Meier survival analysis using log rank test and Cox regression was performed for the entire cohort and a subgroup of older patients, defined as individuals aged 80 years or older. RESULTS:Of the 5,685 patients with vulvar cancer, 3,756 (66.1%) underwent guideline-concordant LN evaluation. In our adjusted model, age 80 years or older (odds ratio [OR], 0.30; 95% CI 0.22-0.42) and Black race (OR 0.72; 95% CI 0.54-0.95) were associated with lower odds of LN evaluation. High-volume hospitals were associated with increased odds of LN evaluation compared with low-volume hospitals (OR 1.62; 95% CI 1.28-2.05). Older individuals who did not undergo LN evaluation had significantly worse overall survival than those with pathologically negative LNs (hazard ratio [HR] 0.45; 95% CI 0.37-0.55) and similar overall survival as those with pathologically positive LNs (HR 1.05; 95% CI 0.77-1.43). CONCLUSION/CONCLUSIONS:Guideline-concordant LN evaluation for early-stage vulvar squamous cell carcinoma is low. Lower utilization is associated with older age, Black race, and care at a low-volume hospital.

INTRODUCTION/BACKGROUND:In gynecologic patients, few studies describe the accuracy of the American College of Surgeons-National Surgical Quality Improvement Project (ACS-NSQIP) pre-operative risk calculator for women undergoing surgery for ovarian cancer. OBJECTIVE:To determine whether the ACS-NSQIP risk calculator accurately predicts post-operative complications and length of stay in patients undergoing interval debulking surgery for advanced stage epithelial ovarian cancer. METHODS:For this multi-institutional retrospective cohort study, pre-operative risk factors, post-operative complication rates, and Current Procedural Terminology codes were abstracted from records of patients with ovarian cancer managed with open interval debulking surgery from January 2010 to July 2015. A power calculation was done to estimate the minimum number of complications needed to evaluate the accuracy of the ACS-NSQIP risk calculator. Predicted risk compared with observed risk was calculated using logistic regression. The predictive accuracy of the ACS-NSQIP risk calculator in estimating post-operative complications or length of stay was assessed using c-statistics and Briar scores. Complications with a c-statistic of >0.70 and Brier score of <0.01 were considered to have high discriminative ability. RESULTS:A total of 261 patients underwent interval debulking surgery, encompassing 21 unique Current Procedural Terminology codes. Readmission (n=25), surgical site infection (n=35), urinary tract infection (n=12), and serious post-operative complications (n=57) met the minimum event threshold (n>10). All predicted complication rates fell within the IQR of the observed incidence rates. However, the ACS-NSQIP calculator demonstrated neither discriminative ability nor accuracy for any post-operative complications based on c-statistics and Brier scores. The calculator accurately predicted length of stay within 1 day for only 32% of patients and could not accurately predict which patients were likely to have a prolonged length of stay (c-statistic=0.65). CONCLUSION/CONCLUSIONS:Among patients undergoing interval debulking surgery, the ACS-NSQIP did not accurately discriminate which patients were at increased risk of complications or extended length of stay. The risk calculator should be considered to have limited utility in informing pre-operative counseling or surgical planning.