SynthesisSystematic reviews2022
Prediction models for breast cancer-related lymphedema: a systematic review and critical appraisal.
Synthesis in Systematic reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Progress and current trends in prediction models for the occurrence and prognosis of cancer and cancer-related complications: a bibliometric and visualization analysis.Frontiers in oncology · 2025Pooled it
- Artificial Intelligence for Prediction of Breast Cancer-Related Lymphedema: A Systematic Review.Plastic and reconstructive surgery. Global open · 2026Article
- Based on the health belief model: a qualitative exploration of factors influencing early screening behavior for breast cancer-related lymphedema.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Using Machine Learning to Predict Breast Cancer-Related Lymphedema Following Axillary Lymph Node Dissection.Annals of surgical oncology · 2026Article
- Development and internal validation of a risk prediction model for ipsilateral upper-limb lymphedema following breast cancer surgery.Frontiers in oncology · 2026Article
- Breast Cancer-Related Lymphedema: Nursing-Led Strategies - A Narrative Review.Journal of multidisciplinary healthcare · 2026Review
- Epidemiological and Clinical Risk Factors for Breast Cancer-Related Lymphedema: A Case-Control Study From Hamadan, Western Iran.BioMed research international · 2026Article
- Identification of chemotherapy-related risk factors for lymphedema in breast cancer patients using Lasso regression and model development.American journal of translational research · 2026Article
- Breast cancer-related lymphedema of the upper limb: integrating early surveillance and functional surgery into a synergistic management paradigm.Frontiers in surgery · 2026Review
- Development and validation of a predictive nomogram for postoperative upper limb lymphedema in breast cancer patients: a retrospective cohort study.Scientific reports · 2025Article
- Optimizing Lymphedema Management After Breast Cancer: Predictive Risk Models in Clinical Practice.Journal of surgical oncology · 2025Article
- Developing the Short-Form of Lymphedema Needs Questionnaire for Iranian Breast Cancer Patients.Cancer medicine · 2025Article
- Breast Cancer-related Lymphedema in Valle del Cauca, Colombia: Prevalence, Risk Factors, and Characterization.Plastic and reconstructive surgery. Global open · 2025Article
- Evaluation of Long-Term Lymphedema Rate in Patients With Subclinical Lymphedema Diagnosed in the Preoperative Period via Bioimpedance.European journal of breast health · 2025Article
- Risk factors and prediction model of breast cancer-related lymphoedema in a Chinese cancer centre: a prospective cohort study protocol.BMJ open · 2024Article
- Development and validation of a nomogram for breast cancer-related lymphedema.Scientific reports · 2024Article
- Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.European urology open science · 2024Review
- Feasibility and Clinical Utility of Prediction Models for Breast Cancer-Related Lymphedema Incorporating Racial Differences in Disease Incidence.JAMA surgery · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe development of risk prediction models for breast cancer lymphedema is increasing, but few studies focus on the quality of the model and its application. Therefore, this study aimed to systematically review and critically evaluate prediction models developed to predict breast cancer-related lymphedema.
methodsPubMed, Web of Science, Embase, MEDLINE, CNKI, Wang Fang DATA, Vip Database, and SinoMed were searched for studies published from 1 January 2000 to 1 June 2021. And it will be re-run before the final analysis. Two independent investigators will undertake the literature search and screening, and discrepancies will be resolved by another investigator. The Prediction model Risk Of Bias Assessment Tool will be used to assess the prediction models' risk of bias and applicability.
resultsSeventeen studies were included in the systematic review, including 7 counties, of which 6 were prospective studies, only 7 models were validation studies, and 4 models were externally validated. The area under the curve of 17 models was 0.680~0.908. All studies had a high risk of bias, primarily due to the participants, outcome, and analysis. The most common predictors included body mass index, radiotherapy, chemotherapy, and axillary lymph node dissection.
conclusionsThe predictive factors' strength, external validation, and clinical application of the breast cancer lymphedema risk prediction model still need further research. Healthcare workers should choose prediction models in clinical practice judiciously. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021258832.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.