Exploring treatment adherence and unmet needs of older breast cancer survival in Nigeria.
Bibliographic record
Abstract
e13849 Background: Breast cancer is the leading cause of cancer death in Nigeria. Older breast cancer patients often experience additional vulnerabilities due to comorbidities, reduced physical resilience, and potential socio-economic limitations that impact their access to chemotherapy, radiotherapy, and targeted therapy. Yet the needs of older breast cancer patients have remained unknown in Nigeria. Hence, this study explored the relationship between unmet needs and treatment adherence among older adults with breast cancer undergoing chemotherapy at a cancer facility in Nigeria. Methods: The participants were (n = 66) people aged 55 to 74 who were undergoing chemotherapy. Data were collected using structured questionnaires and analyzed using descriptive statistics and chi-square tests. Results: The majority were married (53%), and more than half were unemployed (54.5%). Nearly half of the respondents (47%) had an income of less than ₦500,000 per year. In terms of cancer stages, 45.5% of participants were at stage 3, indicating a high prevalence of advanced cancer. The analysis showed that 74.2% of participants reported unmet needs. A significant relationship between unmet needs and treatment compliance was found (χ² = 4.580, p = 0.032). Participants with unmet needs were less likely to exhibit good compliance (77.6%) compared to those whose needs were met (100%). Conclusions: The study highlights the substantial unmet needs among older breast cancer patients, which significantly affect treatment adherence. To enhance treatment adherence and overall quality of life, it is recommended that healthcare providers and policymakers develop targeted interventions to address the specific unmet needs of older cancer patients. This includes improving access to comprehensive care, implementing ASCO practical geriatric assessment, providing socio-economic support, and implementing strategies to manage comorbidities effectively in Nigeria. Key Words: Brest Cancer, Chemotherapy, Older Adults, Unmet Needs, Health Care.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".