Clinical benefits of a multivariate prediction model for bladder cancer: a decision analytic approach

Abstract

Background: It has been demonstrated that multivariate prediction models predict cancer outcomes more accurately than cancer stage; however, the effects of these models on clinical management are unclear. The objective of the current study was to determine whether a previously published multivariate prediction model for bladder cancer ("bladder nomogram") improved medical decision making when referral for adjuvant chemotherapy was used as a model.

Methods: Data were analyzed from an international cohort study of 4462 patients who underwent cystectomy without chemotherapy from 1969 to 2004. The number of patients eligible for chemotherapy was determined using pathologic stage criteria (lymph node-positive disease or pathologic T3 [pT3] or pT4 tumor classification) and for 3 cutoff levels on the bladder nomogram (10%, 25%, and 70% risk of recurrence with surgery alone). The number of recurrences was calculated by applying a relative risk reduction to the baseline risk among eligible patients. Clinical net benefit was then calculated by combining recurrences and treatments and weighting the latter by a factor related to drug tolerability.

Results: A nomogram cutoff outperformed pathologic stage for chemotherapy in every scenario of drug effectiveness and tolerability. For a drug with a relative risk of 0.80, with which clinicians would treat <or=20 patients to prevent 1 recurrence, use of the nomogram was equivalent to a strategy that resulted in 60 fewer chemotherapy treatments per 1000 patients without any increase in recurrence rates.

Conclusions: The authors concluded that referring patients who undergo cystectomy to adjuvant chemotherapy on the basis of a multivariate model is likely to lead to better patient outcomes than the use of pathologic stage. Further research is warranted to evaluate the clinical effects of multivariate prediction models.

Figure 1. Sensitivity analyses

The figure illustrates how relative risk was varied under various assumptions for the relationship between absolute and relative risk. Gray solid line: constant relative risk; gray dashed line: treatment most effective for low risk patients; black dashed line: treatment most effective for high risk patients; black solid line: treatment most effective for average risk patients.

Figure 2. Box plot of nomogram probabilities by pathologic grouping

The box gives the 25^th – 75^th centile, with the median given by the line inside the box. The outside lines give the 5^th and 95^th centiles, with outliers given by dots.

Figure 3. Choice of optimal strategy for administering adjuvant chemotherapy to radical cystectomy patients. Panel A: All patients; Panel B: TCC patients

The shaded areas identify the optimal strategy for each combination of NNT threshold and relative risk. White: administer to all radical cystectomy patients. Light grey: administer to patients with a 5-year probability of recurrence ≥ 10%. Grey: administer to patients with a 5-year probability of recurrence ≥ 25%. Dark grey: administer to patients with a 5-year probability of recurrence ≥ 70%. Black: administer to no patients (intervention does more harm than good). The specificity of the optimal strategy increases from top left to bottom right. Note that the conventional definition was inferior to all other strategies for every combination of NNT threshold and relative risk and therefore has no shaded region on the figure.