ABSTRACT
PURPOSE: Disparities in oral cavity and pharyngeal cancer based on race/ethnicity and socioeconomic status have been reported, but the impact of living within areas that are persistently poor at the time of diagnosis and outcome is unknown. This study aimed to investigate whether the incidence, 5-year relative survival, stage at diagnosis, and mortality among patients with oral cavity and pharyngeal cancers varied by persistent poverty. METHODS: Data were drawn from the SEER database (2006-2017) and included individuals diagnosed with oral cavity and pharyngeal cancers. Persistent poverty (at census tract) is defined as areas where ≥ 20% of the population has lived below the poverty level for ~ 30 years. Age-adjusted incidence and 5-year survival rates were calculated. Multivariable logistic regression was used to estimate the association between persistent poverty and advanced stage cancer. Cumulative incidence and multivariable subdistribution hazard models were used to evaluate mortality risk. In addition, results were stratified by cancer primary site, sex, race/ethnicity, and rurality. RESULTS: Of the 90,631 patients included in the analysis (61.7% < 65 years old, 71.6% males), 8.8% lived in persistent poverty. Compared to non-persistent poverty, patients in persistent poverty had higher incidence and lower 5-year survival rates. Throughout 10 years, the cumulative incidence of cancer death was greater in patients from persistent poverty and were more likely to present with advanced-stage cancer and higher mortality risk. In the stratified analysis by primary site, patients in persistent poverty with oropharyngeal, oral cavity, and nasopharyngeal cancers had an increased risk of mortality compared to the patients in non-persistent poverty. CONCLUSION: This study found an association between oral cavity and pharyngeal cancer outcomes among patients in persistent poverty indicating a multidimensional strategy to improve survival.
ABSTRACT
Abstract Objective: The U.S. Preventive Services Task Force (USPSTF) recommends biennial screening mammography through age 74. Guidelines vary as to whether or not they recommended mammography screening to women aged 75 and older. This study aims to determine the ability of ChatGPT to provide appropriate recommendations for breast cancer screening in patients aged 75 years and older. Methods: 12 questions and 4 clinical vignettes addressing fundamental concepts about breast cancer screening and prevention in patients aged 75 years and older were created and asked to ChatGPT three consecutive times to generate 3 sets of responses. The responses were graded by a multi-disciplinary panel of experts in the intersection of breast cancer screening and aging . The responses were graded as 'appropriate', 'inappropriate', or 'unreliable' based on the reviewer's clinical judgment, content of the response, and whether the content was consistent across the three responses . Appropriateness was determined through a majority consensus. Results: The responses generated by ChatGPT were appropriate for 11/17 questions (64%). Three questions were graded as inappropriate (18%) and 2 questions were graded as unreliable (12%). A consensus was not reached on one question (6%) and was graded as no consensus. Conclusions: While recognizing the limitations of ChatGPT, it has potential to provide accurate health care information and could be utilized by healthcare professionals to assist in providing recommendations for breast cancer screening in patients age 75 years and older. Physician oversight will be necessary, due to the possibility of ChatGPT to provide inappropriate and unreliable responses, and the importance of accuracy in medicine.
ABSTRACT
BACKGROUND: Adiposity and skeletal muscle levels assessed on computed tomography (CT) scans are prognostic indicators for patients with breast cancer. However, the intraindividual reliability of temporal changes in body composition assessed on opportunistic CT scans is unclear. METHODS: This retrospective study included 50 patients newly diagnosed with breast cancer who had archived CT scans pre- and postsurgery for breast cancer. The third lumbar CT image was segmented for areas of 3 types of adipose tissues and 5 different densities of skeletal muscles. Mean and percent changes in areas pre- vs postsurgery were compared using Wilcoxon signed rank tests. Intraclass correlation coefficients (ICCs) with 95% confidence intervals were assessed. A 2-sided P less than .05 was considered statistically significant. RESULTS: Mean (SD) age at diagnosis was 58.3 (12.5) years, and the interval between CT scans was 590.6 (536.8) days. Areas for body composition components were unchanged except for intermuscular adipose tissue (mean change = 1.45 cm2, 6.74% increase, P = .008) and very high-density muscle (mean change = -0.37 cm2, 11.08% decrease, P = .01) during the interval. There was strong intraindividual reliability in adipose tissue and skeletal muscle areas on pre- vs postsurgery scans overall (ICC = 0.763-0.998) and for scans collected 3 or less years apart (ICC = 0.802-0.999; 42 patients). CONCLUSIONS: Although some body composition components may change after breast cancer surgery, CT scan assessments of body composition were reliable for a 3-year interval including the surgery. These findings inform measurement characteristics of body composition on opportunistic CT scans of patients undergoing surgery for breast cancer.
