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Review
. 2015 Apr;16(4):e173-80.
doi: 10.1016/S1470-2045(14)71116-7.

Nomograms in oncology: more than meets the eye

Vinod P Balachandran  1 , Mithat Gonen  2 , J Joshua Smith  3 , Ronald P DeMatteo  3
Affiliations
Review

Nomograms in oncology: more than meets the eye

Vinod P Balachandran et al. Lancet Oncol. 2015 Apr.

Abstract

Nomograms are widely used as prognostic devices in oncology and medicine. With the ability to generate an individual probability of a clinical event by integrating diverse prognostic and determinant variables, nomograms meet our desire for biologically and clinically integrated models and fulfill our drive towards personalised medicine. Rapid computation through user-friendly digital interfaces, together with increased accuracy, and more easily understood prognoses compared with conventional staging, allow for seamless incorporation of nomogram-derived prognosis to aid clinical decision making. This has led to the appearance of many nomograms on the internet and in medical journals, and an increase in nomogram use by patients and physicians alike. However, the statistical foundations of nomogram construction, their precise interpretation, and evidence supporting their use are generally misunderstood. This issue is leading to an under-appreciation of the inherent uncertainties regarding nomogram use. We provide a systematic, practical approach to evaluating and comprehending nomogram-derived prognoses, with particular emphasis on clarifying common misconceptions and highlighting limitations.

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Conflict of interest statement

Conflict of interest: None

Figures

Figure 1
Figure 1. Using and interpreting a nomogram
A. A nomogram example – estimating recurrence-free survival (RFS) in resected primary gastrointestinal stromal tumor (GIST). Draw an upward vertical line to the “Points” bar to calculate points. Based on the sum, draw a downward vertical line from the “Total Points” line to calculate RFS.(14) B. Calibration curves of a nomogram estimating RFS in resected primary GIST. Red line: nomogram RFS = observed RFS. Blue line - actual calibration. Circles - median. X - mean. 95% confidence intervals are depicted for each point along the calibration curve.(14)
Figure 2
Figure 2. Assessing clinical utility using a decision analysis curve
Decision analysis curve of a nomogram predicting seminal vesicle invasion (SVI) in prostate cancer. At a threshold probability of < 5%, > 50%, the nomogram is irrelevant.(32)
See this image and copyright information in PMC

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