Reading list

Applying Propensity Score Methods in Medical Research: Pitfalls and Prospects, by Zhehui Luo, Joseph C. Gardiner, and Cathy J. Bradley.

The authors review experimental and nonexperimental causal inference methods, focusing on assumptions for the validity of instrumental variables and propensity score (PS) methods. They provide guidance in four areas for the analysis and reporting of PS methods in medical research and selectively evaluate mainstream medical journal articles from 2000 to 2005 in the four areas, namely, examination of balance, overlapping support description, use of estimated PS for evaluation of treatment effect, and sensitivity analyses. In spite of the many pitfalls, when appropriately evaluated and applied, PS methods can be powerful tools in assessing average treatment effects in observational studies. Appropriate PS applications can create experimental conditions using observational data when randomized controlled trials are not feasible and, thus, lead researchers to an efficient estimator of the average treatment effect.

Screening for prostate cancer: systematic review and meta-analysis of randomised controlled trials, by Mia Djulbegovic, Rebecca J Beyth, Molly M Neuberger, Taryn L Stoffs, Johannes Vieweg, Benjamin Djulbegovic, Philipp Dahm. See also the recent Boston Globe story.

Objective. To examine the evidence on the benefits and harms of screening for prostate cancer.

Design. Systematic review and meta-analysis of randomised controlled trials.

Data sources. Electronic databases including Medline, Embase, CENTRAL, abstract proceedings, and reference lists up to July 2010.

Review methods. Included studies were randomised controlled trials comparing screening by prostate specific antigen with or without digital rectal examination versus no screening. Data abstraction and assessment of methodological quality with the GRADE approach was assessed by two independent reviewers and verified by the primary investigator. Mantel-Haenszel and inverse variance estimates were calculated and pooled under a random effects model expressing data as relative risks and 95% confidence intervals.

Results. Six randomised controlled trials with a total of 387 286 participants that met inclusion criteria were analysed. Screening was associated with an increased probability of receiving a diagnosis of prostate cancer (relative risk 1.46, 95% confidence interval 1.21 to 1.77; P<0.001) and stage I prostate cancer (1.95, 1.22 to 3.13; P=0.005). There was no significant effect of screening on death from prostate cancer (0.88, 0.71 to 1.09; P=0.25) or overall mortality (0.99, 0.97 to 1.01; P=0.44). All trials had one or more substantial methodological limitations. None provided data on the effects of screening on participants’ quality of life. Little information was provided about potential harms associated with screening.

Conclusions. The existing evidence from randomised controlled trials does not support the routine use of screening for prostate cancer with prostate specific antigen with or without digital rectal examination.

Are Health Insurance Markets Competitive? by Leemore Dafny. If this looks familiar, it is because it came out as an NBER working paper quite a while ago.

To gauge the competitiveness of the group health insurance industry, I investigate whether health insurers charge higher premiums, ceteris paribus, to more profitable firms. Such “direct price discrimination” is feasible only in imperfectly competitive settings. Using a proprietary national database of health plans offered by a sample of large, multisite firms from 1998-2005, I find firms with positive profit shocks subsequently face higher premium growth, even for the same health plans. Moreover, within a given firm, those sites located in concentrated insurance markets experience the greatest premium increases. The findings suggest health care insurers are exercising market power in an increasing number of geographic markets.

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