Clinical Review | Oncology | Breast Cancer

Breast Cancer Lymphoedema: Can a 5-Factor Risk Model Predict 2-Year Survival Accurately?

 

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Originally Published in JAMA,12 January, 2025. This is a summary of the clinical study and in no way represents the original research. Unless otherwise indicated, all work contained here is implicitly referenced to the original author and trial. Links to all original material can be found at the end of this summary. Access the Disclaimer
 

 

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Study Context | Objectives | Study Design | Findings | Discussion| Limitations | Conclusion | Original Research | Funding | References

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In Context 

Breast cancer remains one of the most prevalent malignancies globally, with incidence rates varying across populations. As we previously reported, In South Africa, it is the most common cancer among women, with notably higher rates in the private healthcare sector (110.1 per 100,000 in 2020).¹ Treatment modalities, including surgery, radiation therapy, and systemic therapy, are fundamental to disease management. However, these interventions pose risks, one of the most significant being breast cancer–related lymphedema (BCRL).

For years, BCRL was thought to result solely from axillary lymph node dissection (ALND). However, emerging evidence indicates a multifactorial aetiology incorporating locoregional and systemic treatment strategies, as well as patient-specific biological factors. The ability of an individual to form collateral lymphatic pathways post-injury, alongside modifiable factors such as body mass index (BMI), influences BCRL development. ^{3, 7,11}

Incidence and Timing of BCLR onset

Determining the precise incidence of BCRL is complex due to its variable latency period. The extent of axillary surgery remains a major risk factor, with ALND significantly increasing lymphatic disruption compared to sentinel or regional lymph node biopsies,  potentially quadrupling the rate of BCRL.

In a prospective cohort study of 2,171 women, BCRL onset peaked between 12 and 30 months postoperatively, but timing varied based on treatment:   ^4 ,6,10 

• Early-onset BCRL(<12 months postoperatively) was associated with ALND but not regional lymph node radiation (RLNR) (HR, 1.21; P = .55).
• Late-onset BCRL (>12 months postoperatively) correlated with RLNR and ALND.
• The risk was highest 6–12 months postoperatively in patients undergoing ALND without RLNR, 18–24 months in those receiving ALND plus RLNR, and 36–48 months in those undergoing SLNB plus RLNR. 

These findings highlight the need for treatment-specific screening protocols to facilitate early detection and intervention. 

Challenges in Risk Prediction and a Novel Prognostic Model

Despite the clinical burden of BCRL, existing risk models lack predictive accuracy when applied beyond their original datasets. The Cleveland Clinic Risk Calculator, for example, initially reported an area under the curve (AUC) of 0.7 but dropped to 0.6 upon external validation. Recognising the limitations of prior models, Kwan et al. (2020) developed a five-factor risk assessment model to predict both lymphedema risk and severity. ²

This model incorporates:

1. Mammographic breast density – A novel predictor, with lower-density breasts associated with increased BCRL risk.
2. Body mass index (BMI) – Elevated BMI contributes to increased lymphatic load and impaired drainage.
3. Age – Older age is linked to reduced lymphatic repair capacity.
4. Number of pathological lymph nodes – A higher nodal burden exacerbates lymphatic disruption.
5. ALND status – The extent of axillary clearance remains a primary determinant of risk.

Unlike previous models, the Kwan et al. framework integrates modifiable patient-specific factors, particularly BMI, offering opportunities for risk reduction through tailored interventions. The ongoing challenge lies in externally validating this model in independent breast cancer cohorts.

The researchers of this study, published in the JAMA, on 21 January 2025, sought to determine whether Kwan et al.’s five-factor model could accurately estimate two-year lymphedema-free survival post-treatment, ultimately improving long-term patient outcomes 

 

Study Purpose

This study investigated the external validity of the 5-factor model proposed by Kwan et al,  by applying it to an independent cohort of patients with breast cancer.1

 

  
 

Findings 
 

This study included 101 female patients diagnosed with localised or locoregional breast cancer. The median age of participants was 54.8 years (IQR: 48.8–62.3), with a mean BMI of 26.6 (SD: 5.0).

At two years, the lymphoedema-free survival (LFS) rate for patients classified as low-risk was 97.5% (95% CI, 94.0%-100.0%), indicating a very high probability of remaining free from lymphoedema within the first two years post-treatment.

In contrast, the high-risk group showed a significantly lower LFS rate of 65.0% (95% CI, 47.1%-89.7%) (P < .001), highlighting the model's capacity to accurately differentiate between patients at high and low risk for developing lymphoedema.

This stark difference in survival outcomes was further emphasised by the hazard ratio (HR) of 22.24 (95% CI, 4.80-103.09; P < .001) for the high-risk group relative to the low-risk group. This HR value significantly exceeded the target benchmark of 1.25, indicating a clinically meaningful difference in the lymphoedema-free survival rates between the two groups.

The overall accuracy of the model was 0.88 (95% CI: 0.80-0.94), surpassing the target benchmark of 0.85 for accuracy in predictive models. 

Furthermore, the positive predictive value (PPV) was 0.50 (95% CI, 0.27-0.73), while the negative predictive value (NPV) was particularly high at 0.98 (95% CI, 0.91-1.00), confirming the model's high reliability in ruling out low-risk patients.

These findings underscore the 5-factor model's strong validity and clinical applicability, providing a reliable tool for predicting lymphoedema risk in breast cancer patients and informing early interventions. The model demonstrates significant potential for clinical use, offering a statistically robust approach to risk stratification and providing valuable prognostic information.

 

Discussion

Given the high prevalence of breast cancer and the common occurrence of secondary lymphedema as a complication of its treatment, there is a critical need for reliable tools to help identify patients at risk for developing lymphedema. This prognostic study identified a 5-factor lymphedema risk model that incorporates key patient, cancer, and treatment-related factors. The model was validated in an independent cohort, confirming its ability to predict 2-year lymphoedema-free survival (LFS) accurately and proving its robustness as a tool for clinical use.

Recent clinical practice guidelines have emphasised the importance of early intervention and preventive management for breast cancer-related lymphedema. This model is particularly useful for predicting the risk in patients undergoing axillary lymph node dissection (ALND), enabling clinicians to assess risk before implementing preventive strategies and avoiding overtreatment.

For patients undergoing more limited axillary procedures, this model aids in precise risk stratification. By integrating routine clinical data, the model can divide patients into low- and high-risk groups, facilitating more targeted surveillance and preventative interventions for those at elevated risk.

However, there are some limitations to consider. The sample size in this cohort was relatively small, which may affect the generalizability of the findings. Additionally, the incidence of lymphedema in this cohort reflects primarily early-stage breast cancer patients, meaning the model's effectiveness in predicting severe lymphedema could not be fully validated, as this is a rarer occurrence.


Conclusion

In conclusion, this prospective study of patients with predominantly early-stage breast cancer successfully validated a 5-factor lymphedema risk model for predicting 2-year LFS. The factors included in the model are accessible in routine clinical practice, and the successful external validation of the model suggests its potential for widespread use in clinical settings. This offers a valuable tool for better-identifying patients at risk for lymphedema and improving patient management.

 

 

Access the Study

Lin, C., Su, J., Wu, A. J., Lin, N., Hossack, M. S., Shi, W., Xu, W., Liu, F. F., & Kwan, J. Y. Y. (2025). External Validation of a 5-Factor Risk Model for Breast Cancer-Related Lymphedema. JAMA network open, 8(1), e2455383. https://doi.org/10.1001/jamanetworkopen.2024.55383

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Conflict of Interest, Funding and Support

Role of the Funder/Sponsor
The study's funder had no role in the design, data collection, data analysis, data interpretation, or writing of the report.

Conflict of Interest Disclosures
Full declaration available on original study

Funding/Support
This study was supported by grants from the Temerty Faculty of Medicine, University of Toronto; Department of Radiation Oncology, University of Toronto; and Princess Margaret Cancer Foundation.


References


1. Finestone, E., & Wishnia, J. (2022). Estimating the burden of cancer in South Africa. SA Journal of Oncology, 6(1). https://hdl.handle.net/10520/ejc-sajo_v6_i0_a220
 

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