Literature DB >> 28457319

Validation of a breast cancer nomogram to predict lymphedema in a Chinese population.

Xiaoping Li1, Hui Huang2, Qimou Lin3, Qihe Yu3, Yi Zhou3, Wansheng Long3, Ningxia Wang4.   

Abstract

BACKGROUND: Upper arm lymphedema (LE) is a common complication after axillary lymph node dissection (ALND) in breast cancer patients. This retrospective cohort study aimed to validate a published nomogram to predict the risk of LE in the Chinese breast cancer patients.
METHODS: A total of 409 breast cancer patients who underwent breast cancer surgery and ALND (level I and II) were identified. Cox regression analysis was used to identify the risk factors for LE. The nomogram predictive of LE of breast cancer was evaluated by receiver-operating curve analysis, calibration plots, and Kaplan-Meier analysis in our study population.
RESULTS: With a median follow-up of 68 months, the 5-year cumulative incidence of LE was 22.3%. Higher body mass index (hazard ratio [HR] = 1.06, 95% CI: 1.00-1.13), neoadjuvant chemotherapy (HR = 3.76, 95% CI: 2.29-6.20), larger extend of axillary surgery (level I/II/III versus level I/II: HR = 2.39, 95% CI: 1.30-4.37), and radiotherapy (HR = 4.90, 95% CI: 1.90-12.5) were independently associated with LE. The AUC value of the nomogram was 0.706 (95% CI: 0.648-0.752). A high-risk subgroup of patients defined by nomogram had significantly higher cumulative risk of LE than those in the low-risk subgroups (P < 0.01). The calibration plots revealed that the nomogram was well calibrated (Hosmer-Lemeshow test, P = 0.0634).
CONCLUSIONS: The nomogram to predict the risk of LE in breast cancer patients with ALND has been validated to be discriminative and accurate. More studies are needed to evaluate the impact of other factors (lifestyle, behaviors, and so forth) on the performance of the nomogram.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Axillary lymph node dissection; Breast cancer; Lymphedema; Nomogram

Mesh:

Year:  2016        PMID: 28457319     DOI: 10.1016/j.jss.2016.11.009

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.192


  3 in total

1.  Validation of a nomogram for predicting the risk of lymphedema following contemporary treatment for breast cancer: a large multi-institutional study (KROG 20-05).

Authors:  Hwa Kyung Byun; Jae Sik Kim; Jee Suk Chang; Yeona Cho; Sung-Ja Ahn; Jung Han Yoon; Haeyoung Kim; Nalee Kim; Euncheol Choi; Hyeli Park; Kyubo Kim; Shin-Hyung Park; Chai Hong Rim; Hoon Sik Choi; Yoon Kyeong Oh; Ik Jae Lee; Kyung Hwan Shin; Yong Bae Kim
Journal:  Breast Cancer Res Treat       Date:  2022-02-02       Impact factor: 4.872

2.  Supervised Machine Learning Predictive Analytics For Triple-Negative Breast Cancer Death Outcomes.

Authors:  Yucan Xu; Lingsha Ju; Jianhua Tong; Chengmao Zhou; Jianjun Yang
Journal:  Onco Targets Ther       Date:  2019-11-01       Impact factor: 4.147

3.  A scoring system for predicting the risk of breast cancer-related lymphedema.

Authors:  Fenglian Li; Qian Lu; Sanli Jin; Quanping Zhao; Xueying Qin; Shuai Jin; Lichuan Zhang
Journal:  Int J Nurs Sci       Date:  2019-12-14
  3 in total

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