Faculty Bibliography

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.

PURPOSE/OBJECTIVE:Ovarian-Adnexal Reporting and Data System (O-RADS) MRI uses a 5-point scale to establish malignancy risk in sonographically-indeterminate adnexal masses. The management of O-RADS MRI score 4 lesions is challenging, as the prevalence of malignancy is widely variable (5-90%). We assessed imaging features that may sub-stratify O-RADS MRI 4 lesions into malignant and benign subgroups. METHOD/METHODS:Retrospective single-institution study of women with O-RADS MRI score of 4 adnexal masses between April 2021-August 2022. Imaging findings were assessed independently by 2 radiologists according to the O-RADS lexicon white paper. MRI and clinical findingswere compared between malignant and benign adnexal masses, and inter-reader agreement was calculated. RESULTS:Seventy-four women (median age 52 years, IQR 36-61) were included. On pathology, 41 (55.4%) adnexal masses were malignant. Patients with malignant masses were younger (p = 0.02) with higher CA-125 levels (p = 0.03). Size of solid tissue was greater in malignant masses (p = 0.01-0.04). Papillary projections and larger solid portion were more common in malignant lesions; irregular septations and predominantly solid composition were more frequent in benign lesions (p < 0.01). Solid tissue of malignant lesions was more often hyperintense on T2-weighted and diffusion-weighted imaging (p ≤ 0.03). Other imaging findings were not significantly different (p = 0.09-0.77). Inter-reader agreement was excellent-good for most features (ICC = 0. 662-0.950; k = 0. 650-0.860). CONCLUSION/CONCLUSIONS:Various MRI and clinical features differed between malignant and benign O-RADS MRI score 4 adnexal masses. O-RADS MRI 4 lesions may be sub-stratified (high vs low risk) based on solid tissue characteristics and CA-125 levels.

PURPOSE/UNASSIGNED:Financial toxicity of cancer treatment is well described in the literature, including characterizations of its risk factors, manifestations, and consequences. There is, however, limited research on interventions, particularly those at the hospital level, to address the issue. METHODS/UNASSIGNED:From March 1, 2019, to February 28, 2022, a multidisciplinary team conducted a three-cycle Plan-Do-Study-Act (PDSA) process to develop, test, and implement an electronic medical record (EMR) order set to directly refer patients to a hospital-based financial assistance program. The cycles included an assessment of the efficacy of our current practice in connecting patients experiencing financial hardship with assistance, the development and piloting of the EMR referral order, and the broad implementation of the order set across our institution. RESULTS/UNASSIGNED:In PDSA cycle 1, we found that approximately 25% of patients at our institution experienced some form of financial hardship, but most patients were not connected to available resources because of our referral mechanism. In PDSA cycle 2, the pilot referral order set was deemed feasible and received positive feedback. Over the 12-month study period (March 1, 2021-February 28, 2022) of PDSA cycle 3, 718 orders were placed for 670 unique patients across interdisciplinary providers from 55 treatment areas. These referrals resulted in at least $850,000 in US dollars (USD) in financial aid in 38 patients (mean = $22,368 USD). CONCLUSION/UNASSIGNED:The findings from our three-cycle PDSA quality improvement project demonstrate the feasibility and efficacy of interdisciplinary efforts to develop a hospital-level financial toxicity intervention. A simple referral mechanism can empower providers to connect patients in need with available resources.

Financial toxicity describes the adverse impact patients experience from the monetary and time costs of cancer care. The financial burden patients experience comes from substantially increased out-of-pocket spending that often occurs concurrent with reduced income due to sick leave from work. Financial toxicity is common affecting approximately half of patients with a gynecological cancer depending on the validated instrument used for measurement. Financial toxicity is experienced by patients in three domains: economic hardship affecting patients' material conditions (i.e., medical debt), psychological response (i.e., distress), and health-related coping behaviors that patients adopt (i.e., foregoing care due to costs). Higher financial toxicity among cancer patients has been associated with decreased quality of life, impaired adherence to recommended care, and worse overall survival. In this review, we describe the current literature on financial toxicity, including how it can be assessed with validated tools, the downstream impact on patients, risk factors, and employment concerns of survivors. Whenever possible, we highlight data from research featuring patients with gynecologic cancer specifically. We also review studies with interventions aimed to mitigate financial toxicity and offer the reader real world examples of interventions currently being used. Lastly, we provide an overview of health policy developments relevant to financial toxicity and advocate for innovation in the development and implementation of strategies to decrease the financial toxicity patients experience following a diagnosis of gynecologic cancer.

BACKGROUND:Cancer-related financial hardship can negatively impact financial well-being and may prevent adolescent and young adult (AYA) cancer survivors (ages 15-39) from gaining financial independence. This analysis explored the financial experiences following diagnosis with cancer among AYA survivors. METHODS:We conducted a cross-sectional, anonymous survey of a national sample of AYAs recruited online. The Comprehensive Score for Financial Toxicity (COST) and InCharge Financial Distress/Financial Well-Being Scale (IFDFW) assessed financial hardship (cancer-related and general, respectively), and respondents reported related financial consequences and financial coping behaviors (both medical and non-medical). RESULTS:Two hundred sixty-seven AYA survivors completed the survey (mean 8.3 years from diagnosis). Financial hardship was high: mean COST score was 13.7 (moderate-to-severe financial toxicity); mean IFDFW score was 4.3 (high financial stress). Financial consequences included post-cancer credit score decrease (44%), debt collection contact (39%), spending more than 10% of income on medical expenses (39%), and lacking money for basic necessities (23%). Financial coping behaviors included taking money from savings (55%), taking on credit card debt (45%), putting off major purchases (45%), and borrowing money (42%). In logistic regression models, general financial distress was associated with increased odds of experiencing financial consequences and engaging in both medical- and non-medical-related financial coping behaviors. DISCUSSION/CONCLUSIONS:AYA survivors face long-term financial hardship after cancer treatment, which impacts multiple domains, including their use of healthcare and their personal finances. Interventions are needed to provide AYAs with tools to navigate financial aspects of the healthcare system; connect them with resources; and create systems-level solutions to address healthcare affordability. IMPLICATIONS FOR CANCER SURVIVORS/CONCLUSIONS:Survivorship care providers, particularly those who interact with AYA survivors, must be attuned to the unique risk for financial hardships facing this population and make efforts to increase access available interventions.