Abstract A116: Assessment of equitable care for women of color with mBC
Bibliographic record
Abstract
Abstract MD Anderson Cancer Center at Cooper in collaboration with The Chrysalis Initiative (TCI), sought to characterize the differences between the care that women of color (WOC) receive for metastatic breast cancer (mBC) compared to White women (WW), and understand the social determinants of health (SDOH) and palliative care (PC) needs that WOC with mBC face compared to WW. Twenty-eight WOC and 74 WW with mBC participated in an IRB approved telephone survey. The survey included questions on SDOH, understanding of PC, and the Edmonton System Assessment Scale which assesses symptoms common in cancer patients. WOC with mBC who participated tended to be less often married, more often had non-private insurance, and had lower educational levels and income. The only statistically significant response between the groups was that 50% of the WOC had ever heard of advance directives compared to 86.5% of WW (P<0.001). However, there were concerns for both groups including: 3 in 5 women had issues with lack of transportation to their appointments; 69% reported stress, nervousness, or anxiety; 78% were not following with a palliative care provider; 63% were dealing with pain; 59% were dealing with depression; 58% did not have a living will; 58% had not had an advanced directive discussed with them; 44% never heard of palliative care; and 40% had not had access to a social worker or nurse navigator. Also, TCI led 6 focus groups of women being treated for mBC at Cooper. Three focus groups comprised of 9 WOC with mBC, and 3 consisted of 15 WW with mBC. The goals of the focus groups were to gain insight into the factors influencing patient’s reasoning for their feelings towards the care they receive, and gain insight into the level of knowledge patients have about their breast cancer type, metastatic terminology, and other factors related to their journey. The themes identified suggest that important factors influence patients’ feelings about the care they receive including religion and faith, overall understanding of their treatment plan, willingness to research new treatment options on their own, and lifestyle and support systems that allow them to address and overcome barriers to care. WOC tended to have a poorer appreciation of their breast cancer disease and tumor characteristics and demonstrated lower health literacy or understanding of their mBC characteristics, and the relevance of these in their treatment plans. They had poorer knowledge of available support and palliative care resources and a higher incidence of feeling that they were not being listened to. Focus groups and surveys of women with mBC taught us that poor access to palliative care and social determinants of health disparities are prevalent for persons of color, and that having metastatic breast cancer is a burden for all ethnicities. Efforts need to continue to focus on educating WOC about their disease and its treatment. More importantly, we need to ensure that WOC have access to support services and opportunity to discuss their issues and concerns in a culturally competent manner. Citation Format: Evelyn Robles-Rodriguez, Ashley Weinmann, Generosa Grana, Jamil Rivers. Assessment of equitable care for women of color with mBC [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A116.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".