Faculty Bibliography

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.

BACKGROUND:Sexual orientation and gender identity (SOGI) data collection in community oncology practices is critical to identify and address cancer inequities, but less than 20% of NCI Community Oncology Research Program (NCORP)-affiliated practices regularly collect SOGI data despite widespread recommendations. We evaluated multilevel barriers and facilitators for SOGI data collection at NCORP practices. METHODS:We conducted 14 semi-structured interviews at seven purposefully sampled NCORP oncology practices. We interviewed one clinician (oncologist, advanced practice provider) and one clinic staff member per practice. Thematic analysis informed by the Consolidated Framework for Implementation Research (CFIR) was conducted to identify barriers and facilitators. RESULTS:Thematic saturation occurred after interviews at six practices and was confirmed with interviews at an additional practice. Participants highlighted multilevel barriers including low levels of understanding, information technology infrastructure, and perceived low relative priority. Not understanding the role of SOGI data in oncology care contributed to cis-heteronormative culture. At the clinic level, this culture coincided with a lack of processes and policies for collecting SOGI from all patients. At the care team level, perceived irrelevance to oncology care was related to discomfort asking SOGI, fear of patient discomfort, and limited awareness of SOGI in electronic health records. Suggested solutions included: normalizing asking SOGI questions, giving patients privacy to complete SOGI, and clarifying clinical relevance. CONCLUSIONS:SOGI data collection barriers stemmed from perceptions that SOGI disclosure does not influence care quality. Oncology teams may benefit from training on culturally sensitive SOGI collection, education on SOGI data relevance to oncology practices, and support for implementing SOGI data collection policies.

To identify potential gaps in attitudes, knowledge, and practices towards LGBTQ2S + patients with a cancer diagnosis, a survey of clinical providers (CP) and allied health staff (AHS) was conducted to identify areas of improvement and guide development for future education and training. A previously published, validated survey was adapted at the direction of a LGBTQ2S + Patient and Family Advisory Council, and modified to include AHS. The survey was disseminated to all faculty and staff, and was adapted to the participants' self-identified level of patient interaction/care responsibilities. Subsections consisted of questions related to demographics, knowledge, attitudes, and practice behaviors towards participating in the care of LGBTQ2S + patients. Results were quantified using stratified analysis and an attitude summary measure. Of the 311 respondents, 179 self-identified as CPs and 132 as AHS. There was high agreement in comfort treating or assisting LGBTQ2S + patients by CP and AHS respondents, respectively. CPs possessed significantly higher knowledge regarding LGBTQ2S + health when compared to AHS; however, there remained high percentages of "neutral" and "do not know or prefer not to answer" responses regardless of clinical role. There was high agreement regarding the importance of knowing a patient's gender identity (GI) and pronouns (CP vs. AHS; 76.9% vs. 73.5% and 89.4% vs. 84.1%, respectively), whereas patient's sexual orientation and sex assigned at birth (CP vs. AHS; 51.1% vs. 53.5% and 58.6% vs. 62.9%, respectively) were viewed as less important. There was high interest in receiving education regarding the unique needs of LGBTQ2S + patients regardless of clinical role. Stratified analyses of CPs revealed early-career physicians (< 1-5 years from graduation) expressed higher interest in additional education and involvement with LGBTQ2S + -focused trainings when compared to mid- and late-career providers. This is the first study, to our knowledge, assessing the attitudes, knowledge, and practices of CPs and AHS regarding the care of LGBTQ2S + patients with cancer. Overall, there was high comfort treating/assisting LGBTQ2S + patients among CP and AHS respondents, respectively; yet, both groups possessed significant gaps in LGBTQ2S + -focused knowledge.

Low-stage, low-grade endometrioid endometrial carcinoma (EEC), the most common histologic type of endometrial cancer, typically has a favorable prognosis. A subset of these cancers, however, displays an aggressive clinical course with early recurrences, including distant relapses. All statistical tests were 2-sided. Using a combination of whole-exome and targeted capture sequencing of 65 FIGO stage IA and IB grade 1 EECs treated with surgery alone, we demonstrate that chromosome 1q gain (odds ratio [OR] = 8.09, 95% confidence interval [CI] = 1.59 to 54.6; P = .02), PIK3CA mutation (OR = 9.16, 95% CI = 1.95 to 61.8; P = .01), and DNA mismatch repair-deficient molecular subtype (OR = 7.92, 95% CI = 1.44 to 87.6; P = .02) are independent predictors of early recurrences within 3 years in this patient population. Chromosome 1q gain was validated in an independent dataset of stage I grade 1 EECs subjected to whole-exome sequencing. Our findings expand on the repertoire of genomic parameters that should be considered in the evaluation of patients with low-stage, low-grade EEC.

Sexual and gender minorities (SGM) include persons identifying as lesbian, gay, bisexual, transgender/non-binary, and queer experience a greater cancer burden than their heterosexual or cisgender counterparts. Access to cancer care includes prevention and early detection, however despite known increased risk for various malignancies among SGM individuals, cancer screening rates remain low. This commentary outlines disparities in cancer screening for SGM individuals and provides the current evidence-based screening guidelines for these patients.

Transgender, non-binary, and gender non-conforming people, also referred to as gender minorities, have unique cancer prevention, treatment, and care needs and experience cancer health disparities compared to the cisgender population. We present four composite cases of the cancer care challenges experienced by gender minorities.