Annals of Surgical Oncology

, Volume 22, Issue 3, pp 883–888 | Cite as

Delay in Diagnosis and Treatment of Symptomatic Breast Cancer in China

  • Qiang Huo
  • Chang Cai
  • Yan Zhang
  • Xiaoli Kong
  • Liyu Jiang
  • Tingting Ma
  • Ning Zhang
  • Qifeng YangEmail author
Breast Oncology



Delay in diagnosis and treatment of cancer may lead to advanced tumor characteristics and poor prognosis. Research and investigation from economically developing countries such as China are warranted to support these conclusions, so we studied the impact on prognosis of delays and factors predicting delay in symptomatic breast cancer patients in China.


Medical records and follow-up information were collected. Variables including demographic data, and clinical and tumor characteristics, including patient age, menstrual status, residential status, initial symptom, profession, comorbidities, tumor size, lymph node metastasis, distant metastasis, history of breast disease, and family history of breast cancer, were analyzed, as was survival information.


A total of 1,431 women diagnosed with breast cancers between 1998 and 2005 in Qilu Hospital were enrolled and studied. Delays in diagnosis and treatment were correlated with larger tumor size, lymph node metastasis, late tumor stage, and worse disease-free survival, as assessed by multivariate logistic regression and Kaplan–Meier regression models. Patient residential status, initial symptom, menopausal status, and history of breast disease were independent predictors of delay. Stratified multivariate analyses confirmed that age was not associated with delay.


Delay in diagnosis and treatment predicts worse clinical outcomes. Improvement of medical service in rural areas, especially for premenopausal women, can decrease delays and benefit breast cancer patients.


Breast Cancer Initial Symptom Large Tumor Size Breast Disease Residential Status 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the National Natural Science Foundation of China (30772133; 81072150; 81172529; 81272903) and the Shandong Science and Technology Development Plan (2012GZC22115). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


The authors declare no conflict of interest.

Supplementary material

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Supplementary material 1 (DOC 40 kb)
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Supplementary material 2 (TIFF 718 kb)


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Copyright information

© Society of Surgical Oncology 2014

Authors and Affiliations

  • Qiang Huo
    • 1
    • 2
  • Chang Cai
    • 1
    • 2
  • Yan Zhang
    • 3
  • Xiaoli Kong
    • 1
  • Liyu Jiang
    • 1
  • Tingting Ma
    • 1
  • Ning Zhang
    • 1
  • Qifeng Yang
    • 1
    • 4
    Email author
  1. 1.Department of Breast SurgeryQilu Hospital of Shandong UniversityJinanChina
  2. 2.School of MedicineShandong UniversityJinanChina
  3. 3.Department of NursingQilu Hospital of Shandong UniversityJinanChina
  4. 4.Pathology Tissue BankQilu Hospital of Shandong UniversityJinanChina

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