inst/shinyElicit/Steps.md

In NNTbiomarker: Calculate Design Parameters for Biomarker Validation Studies

DEMO report for Statistical Considerations

Step 1. Introduction: the clinical scenario:

• What is the clinical challenge the biomarker should address?

Prognosis of cutaneous T cell lymphoma (CTCL). In early stages of CTCL, patients (Stages IA-IIA) usually do well and have slowly progressive disease, which does not require aggressive therapy associated with substantial side effects. However, about 15% of these patients have unexpected progressive course and rapid demise..

Step 2. Patients and options :

• Who are the patients to help? What are the clinical decision options?

The biomarker is intended to help CTCL patients in Stages IA-IIA, by identifying who should receive Immediate aggressive treatment and who should receive Standard care.

Step 3. Criterion for a useful biomarker: Defining the NNT discomfort zone:

• What region of NNTs (number needed to treat) make both choices uncomfortable? What NNT's for positive and negative test groups would make thse decision clear-cut? What predictive values for positive and negative tests will give NNT's making the decision clear-cut?

Currently, the proportion of patients who should receive prevalence is number needed to treat to help one (NNT) is The biomarker test will be useful can create a clinical consensus supporting using the test for clinical decisions. if the NNT among test-positive patients, NNTPos, is less than NNTLower = 3, and if the NNT among test-negative patients, NNTNeg, is greater than NNTUpper = 50.

Therefore we choose targets NNTPos = 3 and NNTNeg = 84. This performance should suffice to create a clinical consensus supporting using the test for clinical decisions. These values correspond to positive predictive value = PPV = 0.3333333, and negative predictive value = NPV = 0.9880952.

Step 4. Specific clinical benefit:

• How, in detail, will patients be helped by a test that achieves the criteria?

If the biomarker test achieves these predictive values, the benefit to patients will be a biomarker progression risk model that is able to classify patients into high and low risk groups will enable personalized and more aggressive therapy for the patients at highest risk for progression..

Step 5. Prospective study requirements:

• Given the target predictive values how large should a prospective study be, and how long the follow-up?

The retrospective study will recruit 30 patients. . If the test divides the 30 patients into roughly 50% positive and 50% negative, and if the estimates match the hoped-for values NNTPos = 3 and NNTNeg = 84, then the confidence intervals would be (0.114, 0.577) for PPV, and (0.827, 1) for NPV, or equivalently (1.733, 8.776) for NNTPos, and (5.793, 2.6989145 × 104) for NNTNeg.

Step 6. Retrospective study requirements:

• Given a prevalence value, what sensitivity and specificity do we hope for, and what should the sample sizes be to estimate them sufficiently?

The proportion of patients with rapid progression is assumed to be 8%. Combining that with the target PPV and NPV, the required sensitivity (SN) and specificity (SP) are 88% and 85%, respectively (contra-Bayes Theorem). To get a sense of the accuracy of anticipated estimates in the retrospective (case/control) portion of the study, we consider anticipated results for samples sizes 22 cases and 40 controls. For example, if the estimates SN = 19/22 = 88 % and SP = 34/40 = 85 % are observed, then the corresponding confidence intervals will be (0.679, 0.96) for SN, and (0.717, 0.935) for SP. For NNTPos and for NNTNeg, the Bayes predictive intervals will be (1.875, 4.987) for NNTPos , and (30.724, 244.177) for NNTNeg . (These predictive intervals derive from assuming independent Jeffreys priors for SN and SP, sampling from joint independent posteriors incorporating the anticipated results, and applying Bayes theorem).

NNTbiomarker documentation built on May 1, 2019, 11:15 p.m.