Prognostic factors for patients with skeletal metastases from carcinoma of the breast
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Updated: Mar 26, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
J D Stevenson1, M McNair1, G L Cribb1
1Robert Jones and Agnes Hunt Orthopaedic Hospital, Oswestry, Shropshire, SY10 7AG, UK.
Aims:
Surgical intervention in patients with bone metastases from breast cancer is dependent on the estimated survival of the patient. The purpose of this paper was to identify factors that would predict survival so that specific decisions could be made in terms of surgical (or non-surgical) management.
Methods:
The records of 113 consecutive patients (112 women) with metastatic breast cancer were analysed for clinical, radiological, serological and surgical outcomes. Their median age was 61 years (interquartile range 29 to 90) and the median duration of follow-up was 1.6 years (standard deviation (sd) 1.9, 95% confidence interval (CI) 0 to 5.9). The cumulative one- and five-year rates of survival were 68% and 16% (95% Cl 60 to 77 and 95% CI 10 to 26, respectively).
Results:
Linear discriminant analysis identified a 'quadruple A' predictor of survival by reclassifying the sum of the albumin, adjusted calcium, alkaline phosphatase and age covariates each multiplied by a determined factor. The accuracy of this 'quadruple A' predictor was 90% with a sensitivity of 100% and a specificity of 88%. A receiver operating characteristic (ROC) curve revealed an area under the curve of 79%. Survival analysis for this 'quadruple A' predictor (< = one or > one year survival) was statistically significant using the log rank test (p = 0.0004) and Cox proportional hazard (p = 0.001). Multivariate analysis showed the 'quadruple A' predictor to be the only independent predictor of survival (p = 0.01).
Discussion:
The 'quadruple A' predictor, together with other positive predictors of survival, can be used by oncologists, orthopaedic and breast surgeons to estimate survival and therefore guide management.

