Risk prediction models for breast cancer-related lymphedema: A systematic review and meta-analysis.
Eur J Oncol Nurs
; 64: 102326, 2023 Jun.
Article
in En
| MEDLINE
| ID: mdl-37137249
ABSTRACT
PURPOSE:
To review and critically evaluate currently available risk prediction models for breast cancer-related lymphedema (BCRL).METHODS:
PubMed, Embase, CINAHL, Scopus, Web of Science, the Cochrane Library, CNKI, SinoMed, WangFang Data, VIP Database were searched from inception to April 1, 2022, and updated on November 8, 2022. Study selection, data extraction and quality assessment were conducted by two independent reviewers. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability. Meta-analysis of AUC values of model external validations was performed using Stata 17.0.RESULTS:
Twenty-one studies were included, reporting twenty-two prediction models, with the AUC or C-index ranging from 0.601 to 0.965. Only two models were externally validated, with the pooled AUC of 0.70 (n = 3, 95%CI 0.67 to 0.74), and 0.80 (n = 3, 95%CI 0.75 to 0.86), respectively. Most models were developed using classical regression methods, with two studies using machine learning. Predictors most frequently used in included models were radiotherapy, body mass index before surgery, number of lymph nodes dissected, and chemotherapy. All studies were judged as high overall risk of bias and poorly reported.CONCLUSIONS:
Current models for predicting BCRL showed moderate to good predictive performance. However, all models were at high risk of bias and poorly reported, and their performance is probably optimistic. None of these models is suitable for recommendation in clinical practice. Future research should focus on validating, optimizing, or developing new models in well-designed and reported studies, following the methodology guidance and reporting guidelines.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Breast Neoplasms
/
Lymphedema
Type of study:
Diagnostic_studies
/
Etiology_studies
/
Guideline
/
Prognostic_studies
/
Risk_factors_studies
/
Systematic_reviews
Limits:
Female
/
Humans
Language:
En
Journal:
Eur J Oncol Nurs
Journal subject:
ENFERMAGEM
/
NEOPLASIAS
Year:
2023
Type:
Article