Anthracycline Exposure and Breast Cancer Risk in Female Hodgkin Lymphoma Survivors
Bibliographic record
Abstract
Background Treatment of Hodgkin Lymphoma (HL) is based on a risk-stratification approach and typically involves an anthracycline-based chemotherapy regimen with or without radiotherapy (RT). In female HL survivors, there is a strong association between chest RT and increased risk of breast cancer. However, the impact of chemotherapy agents on this risk has not been extensively studied. Recently, a Dutch cohort study found that doxorubicin exposure is associated with an increased breast cancer risk in a dose dependent manner in female HL survivors (Neppelenbroek et al. 2024). As RT volumes and doses decrease, and the therapeutic focus shifts more towards chemotherapy, it is important to better characterize the toxicity associated with these agents, including anthracyclines. This study aims to evaluate the incidence of breast cancer in female HL survivors treated with anthracyclines. Methods We conducted a retrospective, age-matched population-based cohort study of female HL survivors in Ontario, Canada. We included 1089 females aged 12 to 60 who received anthracycline treatment within a year of HL diagnosis from January 1991 to December 2018. Patients with a history of cancer diagnosis or treatment were excluded. HL survivors were matched to controls (1:4) based on age and excluded if they had a history of cancer. The primary outcome was overall cumulative incidence of breast cancer from anthracycline exposure to December 2023. The incidence of breast cancer was estimated with cumulative incidence functions (CIF). We used a Fine-Gray subdistribution hazard model to estimate the hazard ratio (HR) of breast cancer, with death as a competing risk. Among HL survivors, we evaluated whether a higher cumulative anthracycline dose (>250 mg/m2) was associated with an increased risk of breast cancer, adjusting for chest RT. Results The mean age at anthracycline exposure was 28.56 ± 12.58 years (range 11-60) and median follow-up was 11.13 years (IQR 7.49-15.19). 545 females received a cumulative anthracycline dose ≤ 250 mg/m2 (168.61 ± 45.99) and 544 received ≥ 250 mg/m2 (305.23 ± 41.45). In those that received ≤ 250 mg/m2, 64% received RT within one year of diagnosis (49.4% chest RT). In the ≤ 250 mg/m2 group, 29.6% received RT within one year of diagnosis (25.4% chest RT). In the ≤ 250 mg/m2 group, 17 (3.1%) developed breast cancer 17.35 ± 5.80 years following anthracycline exposure, 38 (7.0%) developed another malignancy and 32 (5.9%) died during follow-up. In the ≥ 250 mg/m2 group, 7 (1.3%) developed breast cancer 13.58 ± 8.23 years following anthracycline exposure, 24 (4.4%) developed another malignancy and 46 (8.5%) died during follow-up. Compared to age-matched controls, cases had a higher incidence of breast cancer (HR: 2.37, 95%CI: 1.43-3.93, p=0.0008) and death (HR: 7.1, 95% CI:4.98-10.1, p<0.0001). Matched unadjusted CIF curves showed that at 15 years, the incidence of breast cancer and death was 1.71% (95% CI 0.83-3.15) and 7.73% (95% CI 6.09-9.61) respectively in cases compared to 1.39% (95%CI 0.96-1.95) and 1.30% (95% CI 0.92-1.7) in controls. At 20 years, the incidence of breast cancer and death was 5.25% (95% CI 2.65-9.13) and 8.06% (95% CI 6.32- 10.06) respectively in cases compared to 1.76% (95% CI 1.22-2.46) and 1.85% (95% CI 1.28- 2.59%) in controls. Subgroup analysis demonstrated that this difference was observed in anthracycline-exposed cases that received chest RT compared to age-matched controls (HR 6.93, 95% CI 3.13-15.36, p<0.001). Cases that did not receive chest RT had a similar breast cancer risk to controls (HR 1.015. 95% CI: 0.47-2.18, p=0.97). Using an age-time scale approach, we found that among HL survivors, patients who received chest RT were at a significantly increased risk of developing breast cancer (HR: 2.99, 95%CI: 1.28-6.99, p=0.0117). Anthracycline dose did not impact this risk when comparing low and high dosage groups (HR 0.45, 95% CI: 0.18-1.12, p=0.085). Conclusions Our study found that female HL survivors remain at an increased risk of developing breast cancer, largely driven by chest radiation, and had reduced overall survival, compared to age-matched controls. However, we did not find a dose-dependent relationship between anthracycline exposure and breast cancer risk; thus, we could not validate previous population-based studies in this setting. This may be limited by the length of follow-up and small number of breast cancer events.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".