Re: Net risk reclassification P values: Valid or misleading?

Journal of the National Cancer Institute

Volumn 107, Issue 1, 2015, Pages

  Pencina, Michael J ^a   Neely, Benjamin ^a   Steyerberg, Ewout W ^b  

^a DUKE CLINICAL RESEARCH INSTITUTE   (United States)

^b ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER; TUMOR MARKER;

AREA UNDER THE CURVE; HAZARD RATIO; LETTER; PRIORITY JOURNAL; RISK ASSESSMENT; STATISTICAL SIGNIFICANCE; HUMAN; PREDICTIVE VALUE; STATISTICAL MODEL;

HUMANS; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; RISK ASSESSMENT; TUMOR MARKERS, BIOLOGICAL;

EID: 84925545746     PISSN: 00278874     EISSN: 14602105     Source Type: Journal    
DOI: 10.1093/jnci/dju355     Document Type: Letter

References (7)

1. Vickers AJ, Cronin AM, Begg CB. One statistical test is sufficient for assessing new predictive markers. BMC Med Res Methodol. 2011;11:13.
2. Demler OV, Pencina MJ, D'Agostino RB Sr. Misuse of DeLong test to compare AUCs for nested models. Statist Med. 2012;31(23):2577-2587.
3. Pencina MJ, D'Agostino RB Sr, Steyerberg E. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Statist Med. 2011;30(1):11-21.
4. Pepe MS, Janes H, Li CI. Net Risk Reclassification P Values: Valid or Misleading? J Natl Cancer Inst. 2014;107(1):dju356 doi:10.1093/jnci/dju356.
5. Pepe MS, Kerr KF, Longton G, Wang Z. Testing for improvement in prediction model performance. Stat Med. 2013;32(9):1467-1482.
6. Pencina MJ, D'Agostino RB, Pencina KM, Janssens ACJW, Greenland P. Interpreting incremental value of markers added to risk prediction models. Am J Epidemiol. 2012;176(6):473-481.
7. Leening MJG, Vedder MM, Witteman JCM, Pencina MJ, Steyerberg EW. Net reclassification improvement: computation, interpretation, and controversies. A literature review and clinician's guide. Ann Intern Med. 2014;160(2):122-131.