Skip to content

Forthcoming App Will Estimate Survival of Patients with Operable Cancer Metastatic to Spine

Key findings

  • In this external validation study, a nomogram created by the Skeletal Oncology Research Group (SORG) accurately estimated 3- and 12-month survival for patients with cancer metastatic to the spine
  • The SORG nomogram was more accurate than other groups' prognostic scoring systems for spinal metastases
  • The SORG algorithm (a different prognostic tool) was not sufficiently accurate at predicting survival
  • A forthcoming website and mobile app will make it convenient for surgeons to estimate survival when considering treatment strategies for individual patients

In 2016, the Skeletal Oncology Research Group (SORG), which includes orthopedic oncologists at Massachusetts General Hospital, published two tools for predicting the survival of individual patients with cancer metastatic to the spine:

  • A nomogram, in which prognostic variables (including continuous variables) are set to a common point scale; this tool informs clinicians of survival probabilities in percentages at three time points
  • An algorithm, which does not accommodate continuous variables and classifies patients based on the number of points

SORG has now validated its nomogram in patients other than those whose data was used to develop it. In the Journal of Surgical Oncology, the group reports that the nomogram is more accurate than other prognostic scoring systems for predicting 3-month and 12-month survival in patients with operable spinal metastases.

Joseph H. Schwab MD, MS, chief, Orthopaedic Spine Surgery at Massachusetts General Hospital, and colleagues in SORG received data on 100 adults who had undergone surgery for spinal metastases at an external institution between January 2014 and September 2014. Like the patients whose data was used to develop the nomogram, these patients had metastatic disease from a solid tumor, lymphoma or multiple myeloma.

The researchers performed area under the curve (AUC) calculations to assess the predictive accuracy of the SORG nomogram and algorithm. They considered the tools sufficiently accurate if the AUC was >0.70.

The SORG nomogram surpassed the validation threshold for prediction of 3-month survival (AUC = 0.74) and 12-month survival (AUC = 0.78) but not for prediction of 1-month survival (AUC = 0.65). The SORG algorithm did not surpass the threshold at any time point (1 month, AUC = 0.56; 3 months, AUC = 0.61; 12 months, AUC = 0.65).

The researchers also determined that in terms of AUC, the SORG nomogram was superior to the Tokuhashi score, Tomita scoreBauer modified score and Ghori score for predicting 3- and 12-month survival. None of the other prognostic systems allows prediction of 1-month survival.

The nomogram correctly estimated 1-month survival in 90% of patients, 3-month survival in 71% and 12-month survival in 78%. Based on these and the other findings, the researchers conclude that the nomogram is suitable for use in prognostication when developing a surgical strategy for a given patient.

The researchers are in the process of creating a website and a mobile app to facilitate use of the nomogram at the point of care.

90%
Percentage of patients with whom the SORG nonogram correctly estimated 1-month survival

Learn about the Orthopaedic Spine Center

Contact the Orthopaedic Spine Center

Related topics

Related

Less invasive spine procedures can reduce adverse events and improve clinical outcomes, taking advantage of new imaging technologies and protocols.

Related

Joseph Schwab, MD, discusses how the Mass General Spine Center is utilizing machine learning algorithms to help patients understand their risks and outcomes for surgical procedures with a personalized approach.