Clinical decision analysis

The clinical decision analysis using decision tree

The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations. The usefulness and limitation including six steps in conducting CDA were reviewed. The application of CDA results should be done under shared decision with patients' value.

Concordance between decision analysis and matching systematic review of randomized controlled trials in assessment of treatment comparisons: a systematic review

Background

Systematic review (SR) of randomized controlled trials (RCT) is the gold standard for informing treatment choice. Decision analyses (DA) also play an important role in informing health care decisions. It is unknown how often the results of DA and matching SR of RCTs are in concordance. We assessed whether the results of DA are in concordance with SR of RCTs matched on patient population, intervention, control, and outcomes.

Methods

We searched PubMed up to 2008 for DAs comparing at least two interventions followed by matching SRs of RCTs. Data were extracted on patient population, intervention, control, and outcomes from DAs and matching SRs of RCTs. Data extraction from DAs was done by one reviewer and from SR of RCTs by two independent reviewers.

Results

We identified 28 DAs representing 37 comparisons for which we found matching SR of RCTs. Results of the DAs and SRs of RCTs were in concordance in 73% (27/37) of cases. The sensitivity analyses conducted in either DA or SR of RCTs did not impact the concordance. Use of single (4/37) versus multiple data source (33/37) in design of DA model was statistically significantly associated with concordance between DA and SR of RCTs.

Conclusions

Our findings illustrate the high concordance of current DA models compared with SR of RCTs. It is shown previously that there is 50% concordance between DA and matching single RCT. Our study showing the concordance of 73% between DA and matching SR of RCTs underlines the importance of totality of evidence (i.e. SR of RCTs) in the design of DA models and in general medical decision-making.

Why do physicians switch from one antipsychotic agent to another? The "physician drug stereotype"

There is a lack of research on why physicians select a certain drug in an individual case and not another available alternative, although this drug selection process is important for quality assurance and cost control. Four hundred ninety-five psychiatrists documented in a standardized form patient and illness characteristics of 1711 schizophrenic outpatients who were switched for individual clinical reasons from an ongoing neuroleptic treatment to olanzapine, and of another 1654 schizophrenic outpatients whose present neuroleptic medication was continued. Physicians also filled in the "Reason for Treatment Selection Questionnaire." Patients who were switched to olanzapine were more ill and showed more preexisting extrapyramidal symptoms and less patient compliance. Reasons of psychiatrists to switch to olanzapine were the expectation of better efficacy and tolerability of the present treatment and patient preferences to continue with the present medication. The price of olanzapine is seen as a reason not to select olanzapine but has no effect on the treatment decision. The "physician drug stereotype" of olanzapine corresponds with clinical data on the efficacy and tolerability of olanzapine. The data show that medical decisions about drug selection are multidimensional, integrating knowledge about the clinical properties of the drug, personal experiences and information about the individual case. The Reason for Treatment Selection Questionnaire is an instrument that allows to objectively assess important aspects of medical decision making, to generate psychological drug profile, and to understand why physicians prefer one drug over alternatives.

Pilot Study of a Utilities-Based Treatment Decision Intervention for Prostate Cancer Patients

This pilot study evaluates a shared decision-making approach to individual decision making in localized prostate cancer care. The approach is based on a decision analytic model that incorporates patient utilities, ie, patient preferences among possible health states that might occur with prostate cancer treatments. Data on comorbidities, histologic grade of the biopsy, and age were obtained for 13 patients with newly diagnosed localized prostate cancer who received care in a Veterans Administration medical center. Using a standard gamble technique, interviewers obtained patient utilities for 5 distinct health states related to prostate cancer treatment. Utilities and patient clinical and pathologic characteristics were incorporated into the decision analytic model, and the derived quality-adjusted life expectancies were shared with the treating urologist before the first patient-physician discussion about treatment options. The results of the pilot study raised 2 major concerns. First, 4 patients had utility scores of 1.0 for all of the possible health states, and 7 patients had inconsistent utilities in which they rated both impotence and incontinence as a better health state than having just one of these problems. Second, the model recommended radiation therapy to individuals with a broad range of clinical characteristics, pathologic findings, and utility scores. Many of the patients who were recommended radiation therapy by the model received discordant recommendations from the treating urologist. Future refinements of both the utility assessment exercise and decision analytic model may be needed before the feasibility of the model in the clinical setting can be determined.