Hidden Costs in Breast Cancer-Related Lymphedema

Temporal validation of a risk prediction model for breast cancer-related lymphoedema in European population: A retrospective study

AIMS

To perform temporal validation of a risk prediction model for breast cancer-related lymphoedema in the European population.

DESIGN

Temporal validation of a previously developed prediction model using a new retrospective cohort of women who had undergone axillary lymph node dissection between June 2018 and June 2020.

METHODS

We reviewed clinical records to identify women who did and did not develop lymphoedema within 2 years of surgery and to gather data regarding the variables included in the prediction model. The model was calibrated by calculating Spearman's correlation between observed and expected cases. Its accuracy in discriminating between patients who did versus did not develop lymphoedema was assessed by calculating the area under the receiver operating characteristic curve (AUC).

RESULTS

The validation cohort comprised 154 women, 41 of whom developed lymphoedema within 2 years of surgery. The value of Spearman's coefficient indicated a strong correlation between observed and expected cases. Sensitivity of the model was higher than in the derivation cohort, as was the value of the AUC.

CONCLUSION

The model shows a good capacity to discriminate women at risk of lymphoedema and may therefore help in developing improved care pathways for individual patients.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Identifying risk factors for lymphoedema secondary to breast cancer treatment is vital given its impact on women's physical and emotional well-being.

IMPACT

What problem did the study address? Risk of BCRL. What were the main findings? The prediction model has a good capacity to discriminate women at risk of lymphoedema. Where and on whom will the research have an impact? In clinical practice with women at risk of BCRL.

REPORTING METHOD

STROBE checklist. WHAT DOES THIS PAPER CONTRIBUTE TO THE WIDER GLOBAL CLINICAL COMMUNITY?: It presents a validated risk prediction model for BCRL.

NO PATIENT OR PUBLIC CONTRIBUTION

There was no patient or public contribution in the conduct of this study.

Breast cancer-related lymphoedema: Risk factors and prediction model

AIMS

To identify the risk factors for lymphoedema following axillary lymph node dissection (ALND) in a European sample and to propose a lymphoedema prediction model for this population.

DESIGN

Predictive retrospective cohort study comparing women who developed lymphoedema in 2 years of undergoing ALND with those who did not developed lymphoedema.

METHODS

We reviewed the clinical records of 504 women who, between January 2008 and May 2018, underwent surgery for breast cancer that involved ALND. Logistic regression was used to identify significant risk factors for lymphoedema. The prediction accuracy of the model was assessed by calculating the area under the receiver operating characteristic curve.

RESULTS

Of the 504 women whose records were analysed, 156 developed lymphoedema. Significant predictors identified in the regression model were level of lymph node dissection, lymph node status, post-operative complications, body mass index (BMI) and number of lymph nodes extracted. The prediction model showed good sensitivity (80%) in the study population.

CONCLUSIONS

The factor contributing most to the risk of lymphoedema was the level of lymph node dissection, and the only patient-related factor in the prediction model was BMI. The model offers good predictive capacity in this population and it is a simple tool that breast care units could use to assess the risk of lymphoedema following ALND. Nurses with specialist knowledge of lymphoedema have a key role to play in ensuring that women receive holistic and individualized care.

IMPACT

What problem did the study address? Secondary lymphoedema is one of the main complications in the treatment of breast cancer. What were the main findings? The prediction model included five factors associated with the risk of lymphoedema following ALND. The strongest predictor was the level of lymph node dissection, and the only patient-related factor was BMI. Where and on whom will the research have an impact? The prediction model offers breast care units a tool for assessing the risk of lymphoedema in women undergoing surgery involving ALND. The results highlight the importance of weight reduction as a preventive measure and support a more conservative surgical approach.