Persistent poverty disparities in incidence and outcomes among oral and pharynx cancer patients

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.

Evaluating ChatGPT's Accuracy in Providing Screening Mammography Recommendations among Older Women: Artificial Intelligence and Cancer Communication

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.

Intraindividual Reliability of Opportunistic Computed Tomography-Assessed Adiposity and Skeletal Muscle among Breast Cancer Patients

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.

Abstract 3219: Changes and intra-individual reliability in computed tomography image-assessed adiposity and skeletal muscles areas after breast cancer surgery

Background: Levels of adiposity and skeletal muscles are prognostic indicators in breast cancer patients; however, data are limited on temporal changes in body composition, particularly in different densities of muscles, before and after mastectomy.

Objectives: We examined the change in CT-assessed adipose tissue and different density of skeletal muscle areas using a high-resolution segmentation method in breast cancer patients before and after surgery.

Methods: This study included 50 newly-diagnosed breast cancer patients who had taken CT scans before and after surgery. We analyzed their third lumbar (L3) CT images to measure the areas of adipose tissue and five-level (from very-high-density to very-low-density) skeletal muscle components. We assessed mean and percent changes in areas using paired t-test and calculated the intra-class correlation (ICC).

Results: Patients’ mean age at diagnosis was 58.3 (SD=12.5) years. The mean duration between scans was 591 (SD=537) days. There was a significant decrease in the areas of subcutaneous adipose tissue (mean change= -36.17 cm2, 11.72% decrease, p=0.029), total adipose tissue (mean change= -45.64 cm2, 10.18% decrease, p=0.032), and very-high-density muscle (mean change= -0.37 cm2, 11.08% decrease, p=0.010). The ratio of total adipose tissue and total skeletal muscle decreased from 3.67 to 3.32 after surgery (mean change= -0.36, 9.81% decrease, p=0.061). There was a strong correlation in adipose tissues and skeletal muscle areas of pre-and post-surgery scans taken within 3 years apart (ICC=0.802 to 0.999, all p&lt;0.05), but the correlations were attenuated in scans taken &gt;3 years apart (ICC = -0.055 to 0.738, all p&gt;0.05).

Conclusion: In this sample of breast cancer patients who have undergone surgery, there was a significant decrease in subcutaneous adipose tissues, total adipose tissues, and very-high-density muscle areas over time. Body composition assessed by CT images is reliable for a 3- year period involving breast cancer surgery. These findings serve as a baseline for prospective studies examining the impact of these changes on breast cancer outcomes.

Keywords: Adipose tissue, skeletal muscle, computed tomography scans, breast cancer, surgery

Citation Format: Livingstone Aduse-Poku, Dheeraj Gopireddy, Mauricio Henandez, Chandana Lall, Joel Divaker, Sara Falzarano, Shahla Masood, Weizhou Zhang, Susmita Datta, Jiang Bian, Ting-Yuan David Cheng. Changes and intra-individual reliability in computed tomography image-assessed adiposity and skeletal muscles areas after breast cancer surgery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3219.