The Covariance Decomposition of the Probability Score and Its Use in Evaluating Prognostic Estimates

Hr, Arkes; Nv, Dawson; Speroff, Theodore; Fe, Harrell; Alzola, Carlos; Phillips, Russell S.; Desbiens, Norman A.; Rk, Oye; Knaus, W.; Connors, Alfred F.

doi:10.1177/0272989x9501500204

Cited by 113 publications

(9 citation statements)

References 27 publications

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“…A strong emotional fear of cancer and the desire for an urgent peace of mind can lead to a rash decision about screening when it is presented as an immediate option. Patients may also have difficulty assessing probabilities, and as a result are often overly optimistic about their own outcome when faced with the probabilities of survival with treatment options [36] and overestimate their risk of disease. For example, it has been reported that some men overestimate their lifetime risk of developing and dying from prostate cancer [37].…”

Section: Discussionmentioning

confidence: 99%

Applying strategies from libertarian paternalism to decision making for prostate specific antigen (PSA) screening

2011

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BackgroundDespite the recent publication of results from two randomized clinical trials, prostate specific antigen (PSA) screening for prostate cancer remains a controversial issue. There is lack of agreement across studies that PSA screening significantly reduces prostate cancer mortality. In spite of these facts, the widespread use of PSA testing in the United States leads to overdetection and overtreatment of clinically indolent prostate cancer, and its associated harms of incontinence and impotence.DiscussionGiven the inconclusive results from clinical trials and incongruent PSA screening guidelines, the decision to screen for prostate cancer with PSA testing is an uncertain one for patients and health care providers. Screening guidelines from some health organizations recommend an informed decision making (IDM) or shared decision making (SDM) approach for deciding on PSA screening. These approaches aim to empower patients to choose among the available options by making them active participants in the decision making process. By increasing involvement of patients in the clinical decision-making process, IDM/SDM places more of the responsibility for a complex decision on the patient. Research suggests, however, that patients are not well-informed of the harms and benefits associated with prostate cancer screening and are also subject to an assortment of biases, emotion, fears, and irrational thought that interferes with making an informed decision. In response, the IDM/SDM approaches can be augmented with strategies from the philosophy of libertarian paternalism (LP) to improve decision making. LP uses the insights of behavioural economics to help people better make better choices. Some of the main strategies of LP applicable to PSA decision making are a default decision rule, framing of decision aids, and timing of the decision. In this paper, we propose that applying strategies from libertarian paternalism can help with PSA screening decision-making.SummaryOur proposal to augment IDM and SDM approaches with libertarian paternalism strategies is intended to guide patients toward a better decision about testing while maintaining personal freedom of choice. While PSA screening remains controversial and evidence conflicting, a libertarian-paternalism influenced approach to decision making can help prevent the overdiagnosis and overtreatment of prostate cancer.

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Section: Discussionmentioning

confidence: 99%

Applying strategies from libertarian paternalism to decision making for prostate specific antigen (PSA) screening

2011

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“…We anticipate that the observed and predicted occurrence of PrUs will be similar across the risk groups. A perfect calibration (ie, perfect agreement between the predicted and observed outcomes) will produce a calibration line with an intercept and slope of 0 and 1, respectively [ 27 - 29 ]. The smooth curve will be added to reveal differential calibration among risk deciles, if present.…”

Section: Methodsmentioning

confidence: 99%

Leveraging Electronic Health Care Record Information to Measure Pressure Ulcer Risk in Veterans With Spinal Cord Injury: A Longitudinal Study Protocol

Luther¹,

Thomason²,

Sabharwal³

et al. 2017

JMIR Res Protoc

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BackgroundPressure ulcers (PrUs) are a frequent, serious, and costly complication for veterans with spinal cord injury (SCI). The health care team should periodically identify PrU risk, although there is no tool in the literature that has been found to be reliable, valid, and sensitive enough to assess risk in this vulnerable population.ObjectiveThe immediate goal is to develop a risk assessment model that validly estimates the probability of developing a PrU. The long-term goal is to assist veterans with SCI and their providers in preventing PrUs through an automated system of risk assessment integrated into the veteran’s electronic health record (EHR).MethodsThis 5-year longitudinal, retrospective, cohort study targets 12,344 veterans with SCI who were cared for in the Veterans Health Administration (VHA) in fiscal year (FY) 2009 and had no record of a PrU in the prior 12 months. Potential risk factors identified in the literature were reviewed by an expert panel that prioritized factors and determined if these were found in structured data or unstructured form in narrative clinical notes for FY 2009-2013. These data are from the VHA enterprise Corporate Data Warehouse that is derived from the EHR structured (ie, coded in database/table) or narrative (ie, text in clinical notes) data for FY 2009-2013.ResultsThis study is ongoing and final results are expected in 2017. Thus far, the expert panel reviewed the initial list of risk factors extracted from the literature; the panel recommended additions and omissions and provided insights about the format in which the documentation of the risk factors might exist in the EHR. This list was then iteratively refined through review and discussed with individual experts in the field. The cohort for the study was then identified, and all structured, unstructured, and semistructured data were extracted. Annotation schemas were developed, samples of documents were extracted, and annotations are ongoing. Operational definitions of structured data elements have been created and steps to create an analytic dataset are underway.ConclusionsTo our knowledge, this is the largest cohort employed to identify PrU risk factors in the United States. It also represents the first time natural language processing and statistical text mining will be used to expand the number of variables available for analysis. A major strength of this quantitative study is that all VHA SCI centers were included in the analysis, reducing potential for selection bias and providing increased power for complex statistical analyses. This longitudinal study will eventually result in a risk prediction tool to assess PrU risk that is reliable and valid, and that is sensitive to this vulnerable population.

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“…Accuracy will be assessed with Nagelkerke’s R 2 47 and the Brier score. 48 Discrimination will be assessed using the concordance statistic. Model calibration is especially important in the development of prognostic models, as probabilities of future risk are of primary interest.…”

Section: Methods and Analysismentioning

confidence: 99%

Dementia Population Risk Tool (DemPoRT): study protocol for a predictive algorithm assessing dementia risk in the community

et al. 2017

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IntroductionThe burden of disease from dementia is a growing global concern as incidence increases dramatically with age, and average life expectancy has been increasing around the world. Planning for an ageing population requires reliable projections of dementia prevalence; however, existing population projections are simple and have poor predictive accuracy. The Dementia Population Risk Tool (DemPoRT) will predict incidence of dementia in the population setting using multivariable modelling techniques and will be used to project dementia prevalence.Methods and analysisThe derivation cohort will consist of elderly Ontario respondents of the Canadian Community Health Survey (CCHS) (2001, 2003, 2005 and 2007; 18 764 males and 25 288 females). Prespecified predictors include sociodemographic, general health, behavioural, functional and health condition variables. Incident dementia will be identified through individual linkage of survey respondents to population-level administrative healthcare databases (1797 and 3281 events, and 117 795 and 166 573 person-years of follow-up, for males and females, respectively, until 31 March 2014). Using time of first dementia capture as the primary outcome and death as a competing risk, sex-specific proportional hazards regression models will be estimated. The 2008/2009 CCHS survey will be used for validation (approximately 4600 males and 6300 females). Overall calibration and discrimination will be assessed as well as calibration within predefined subgroups of importance to clinicians and policy makers.Ethics and disseminationResearch ethics approval has been granted by the Ottawa Health Science Network Research Ethics Board. DemPoRT results will be submitted for publication in peer-review journals and presented at scientific meetings. The algorithm will be assessable online for both population and individual uses.Trial registration numberClinicalTrials.govNCT03155815, pre-results.

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The Covariance Decomposition of the Probability Score and Its Use in Evaluating Prognostic Estimates

Cited by 113 publications

References 27 publications

Applying strategies from libertarian paternalism to decision making for prostate specific antigen (PSA) screening

Applying strategies from libertarian paternalism to decision making for prostate specific antigen (PSA) screening

Leveraging Electronic Health Care Record Information to Measure Pressure Ulcer Risk in Veterans With Spinal Cord Injury: A Longitudinal Study Protocol

Dementia Population Risk Tool (DemPoRT): study protocol for a predictive algorithm assessing dementia risk in the community

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