Influence of gender modality on the delivery of breast cancer care from diagnosis to treatment: A systematic review
Bibliographic record
Abstract
Background: Breast cancer is a global health burden. Although screening and treatment programs have improved breast cancer survival for Canadians, it is unclear if there is a disparity in cancer burden and care received by transgender and Two-Spirit patients due to the general paucity of research concerning breast cancer care of these individuals. Objective/Aims: A systematic review was conducted to examine the burden of breast cancer in transgender and Two-Spirit populations, identify how gender modality/identity may impact the delivery of breast cancer care, and develop actionable recommendations for the provision of more inclusive, high-quality cancer care. Methods: A comprehensive search of PubMed/MEDLINE (OVID), Embase (OVID), and Web of Science databases was conducted using keywords and based on the PRISMA framework. Two independent reviewers performed selection and data extraction of studies that met inclusion criteria related to breast cancer in adult transgender and/or Two-Spirit patients. Results: Of 7,402 articles screened, 61 studies were included, the majority of which focused on binary-identified trans people, with none addressing Two-Spirit people’s experiences of cancer care. Findings determined no clear association between gender affirming hormone therapy and risk of breast cancer in transgender populations. Additionally, the burden of breast cancer could be identified for transgender and/or Two-Spirit patients. Patient-provider and system barriers in the delivery of breast cancer care were identified, including lack of trust and knowledge, discrimination, and insufficient population-wide data collection and research. Conclusion: Significant gaps in literature regarding the experiences, barriers and needs of transgender and/or Two-Spirit patients with breast cancer exist. Developing effective guidelines and clinical practices that encompass all gender identities and expanding the depth and scope of research is crucial toward fostering diverse, inclusive, and equitable healthcare.
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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 | 0.008 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".