Insights into different results from different causal contrasts in the presence of effect-measure modification

Purpose: Both propensity score (PS) matching and inverse probability of treatment weighting (IPTW) allow causal contrasts, albeit different ones. In the presence of effect-measure modification, different analytic approaches produce different summary estimates. Methods: We present a spreadsheet example that assumes a dichotomous exposure, covariate, and outcome. The covariate can be a confounder or not and a modifier of the relative risk (RR) or not. Based on expected cell counts, we calculate RR estimates using five summary estimators: Mantel-Haenszel (MH), maximum likelihood (ML), the standardized mortality ratio (SMR), PS matching, and a common implementation of IPTW. Results: Without effect-measure modification, all approaches produce identical results. In the presence of effect-measure modification and regardless of the presence of confounding, results from the SMR and PS are identical, but IPTW can produce strikingly different results (e.g., RR = 0.83 vs. RR = 1.50). In such settings, MH and ML do not estimate a population parameter and results for those measures fall between PS and IPTW. Conclusions: Discrepancies between PS and IPTW reflect different weighting of stratum-specific effect estimates. SMR and PS matching assign weights according to the distribution of the effect-measure modifier in the exposed subpopulation, whereas IPTW assigns weights according to the distribution of the entire study population. In pharmacoepidemiology, contraindications to treatment that also modify the effect might be prevalent in the population, but would be rare among the exposed. In such settings, estimating the effect of exposure in the exposed rather than the whole population is preferable

A community change in the algal endosymbionts of a scleractinian coral following a natural bleaching event: field evidence of acclimatization

The symbiosis between reef-building corals and their algal endosymbionts (zooxanthellae of the genus Symbiodinium) is highly sensitive to temperature stress, which makes coral reefs vulnerable to climate change. Thermal tolerance in corals is known to be substantially linked to the type of zooxanthellae they harbour and, when multiple types are present, the relative abundance of types can be experimentally manipulated to increase the thermal limits of individual corals. Although the potential exists for this to translate into substantial thermal acclimatization of coral communities, to date there is no evidence to show that this takes place under natural conditions. In this study, we show field evidence of a dramatic change in the symbiont community of Acropora millepora, a common and widespread Indo-Pacific hard coral species, after a natural bleaching event in early 2006 in the Keppel Islands (Great Barrier Reef). Before bleaching, 93.5% (n=460) of the randomly sampled and tagged colonies predominantly harboured the thermally sensitive Symbiodinium type C2, while the remainder harboured a tolerant Symbiodinium type belonging to clade D or mixtures of C2 and D. After bleaching, 71% of the surviving tagged colonies that were initially C2 predominant changed to D or C1 predominance. Colonies that were originally C2 predominant suffered high mortality (37%) compared with D-predominant colonies (8%). We estimate that just over 18% of the original A. millepora population survived unchanged leaving 29% of the population C2 and 71% D or C1 predominant six months after the bleaching event. This change in the symbiont community structure, while it persists, is likely to have substantially increased the thermal tolerance of this coral population. Understanding the processes that underpin the temporal changes in symbiont communities is key to assessing the acclimatization potential of reef corals

Mycobacterium tuberculosis lineage: a naming of the parts

There have been many reports of groups of related Mycobacterium tuberculosis strains described variously as lineages, families or clades. There is no objective definition of these groupings making it impossible to define relationships between those groups with biological advantages. Here we describe two groups of related strains obtained from an epidemiological study in Tanzania which we define as the Kilimanjaro and Meru lineages on the basis of IS6110 restriction fragment length polymorphism (RFLP), polymorphic GC rich sequence (PGRS) RFLP and mycobacterial interspersed repeat unit (MIRU) typing. We investigated the concordance between each of the typing techniques and the dispersal of the typing profiles from a core pattern. The Meru lineage is more dispersed than the Kilimanjaro lineage and we speculate that the Meru lineage is older. We suggest that this approach provides an objective definition that proves robust in this epidemiological study. Such a framework will permit associations between a lineage and clinical or bacterial phenomenon to be tested objectively. This definition will also enable new putative lineages to be objectively tested

Effects of interleukin-1β Inhibition on blood pressure, incident hypertension, and residual inflammatory risk

While hypertension and inflammation are physiologically inter-related, the effect of therapies that specifically target inflammation on blood pressure is uncertain. The recent CANTOS (Canakinumab Anti-inflammatory Thrombosis Outcomes Study) afforded the opportunity to test whether IL (interleukin)-1β inhibition would reduce blood pressure, prevent incident hypertension, and modify relationships between hypertension and cardiovascular events. CANTOS randomized 10 061 patients with prior myocardial infarction and hsCRP (high sensitivity C-reactive protein) ≥2 mg/L to canakinumab 50 mg, 150 mg, 300 mg, or placebo. A total of 9549 trial participants had blood pressure recordings during follow-up; of these, 80% had a preexisting diagnosis of hypertension. In patients without baseline hypertension, rates of incident hypertension were 23.4, 26.6, and 28.1 per 100-person years for the lowest to highest baseline tertiles of hsCRP (P>0.2). In all participants random allocation to canakinumab did not reduce blood pressure (P>0.2) or incident hypertension during the follow-up period (hazard ratio, 0.96 [0.85–1.08], P>0.2). IL-1β inhibition with canakinumab reduces major adverse cardiovascular event rates. These analyses suggest that the mechanisms underlying this benefit are not related to changes in blood pressure or incident hypertension

Classifying medical histories in US medicare beneficiaries using fixed vs all‐available look‐back approaches

Purpose: Evaluate use of fixed and all‐available look‐backs to identify eligibility criteria and confounders among Medicare beneficiaries. Methods: We identified outpatient visits (2007‐2012) with recently documented (≤180 days) cardiovascular risk and classified patients according to whether the exposure (statin) was initiated within 14 days. We selected each beneficiary's first eligible visit (in each treatment group) that met criteria during the respective look‐backs: continuous enrollment (1 or 3 years for fixed look‐back; 180 days for all‐available), no cancer history, and no statin claims. We estimated crude and standardized mortality ratio weighted hazard ratios (HRs) for the effect of statin initiation on incident 6‐month cancer (a known null effect) and 2‐year mortality, separately, adjusting for covariates assessed by using each look‐back. Results: Analyzing short‐term cancer, the estimated HR from the all‐available approach (HR = 0.90, 95% CI: 0.83, 0.98) was less biased than the 1‐year look‐back (HR = 0.79, 95% CI: 0.73, 0.84), which included beneficiaries with prevalent cancer. The 3‐year look‐back (HR = 1.05, 95% CI: 0.90, 1.21) was somewhat less biased than the all‐available estimate but less precise due the exclusion of a large proportion of observations without sufficient continuous enrollment (62.0% and 59.9% of initiators and non‐initiators, respectively). All approaches produced similar estimates of the effect on all‐cause mortality. Alternative look‐backs did not differ in their ability to control confounding. Conclusions: The all‐available look‐back performed nearly as well as the 3‐year fixed, which produced the least biased point estimate. If 3‐year look‐backs are infeasible (eg, due to power/sample), all‐available look‐backs may be preferable to short (1‐year) fixed look‐backs

Performance of propensity score calibration - A simulation study

Confounding can be a major source of bias in nonexperimental research. The authors recently introduced propensity score calibration (PSC), which combines propensity scores and regression calibration to address confounding by variables unobserved in the main study by using variables observed in a validation study. Here, the authors assess the performance of PSC using simulations in settings with and without violation of the key assumption of PSC: that the error-prone propensity score estimated in the main study is a surrogate for the gold-standard propensity score (i.e., it contains no additional information on the outcome). The assumption can be assessed if data on the outcome are available in the validation study. If data are simulated allowing for surrogacy to be violated, results depend largely on the extent of violation. If surrogacy holds, PSC leads to bias reduction between 32% and 106% (>100% representing overcorrection). If surrogacy is violated, PSC can lead to an increase in bias. Surrogacy is violated when the direction of confounding of the exposure-disease association caused by the unobserved variable(s) differs from that of the confounding due to observed variables. When surrogacy holds, PSC is a useful approach to adjust for unmeasured confounding using validation data

Analytic strategies to adjust confounding using exposure propensity scores and disease risk scores: Nonsteroidal antiinflammatory drugs and short-term mortality in the elderly

Little is known about optimal application and behavior of exposure propensity scores (EPS) in small studies. In a cohort of 103,133 elderly Medicaid beneficiaries in New Jersey, the effect of nonsteroidal antiinflammatory drug use on 1-year all-cause mortality was assessed (1995-1997) based on the assumption that there is no protective effect and that the preponderance of any observed effect would be confounded. To study the comparative behavior of EPS, disease risk scores, and "conventional" disease models, the authors randomly resampled 1,000 subcohorts of 10,000, 1,000, and 500 persons. The number of variables was limited in disease models, but not EPS and disease risk scores. Estimated EPS were used to adjust for confounding by matching, inverse probability of treatment weighting, stratification, and modeling. The crude rate ratio of death was 0.68 for users of nonsteroidal antiinflammatory drugs. "Conventional" adjustment resulted in a rate ratio of 0.80 (95% confidence interval: 0.77, 0.84). The rate ratio closest to 1 (0.85) was achieved by inverse probability of treatment weighting (95% confidence interval: 0.82, 0.88). With decreasing study size, estimates remained further from the null value, which was most pronounced for inverse probability of treatment weighting (n = 500: rate ratio = 0.72, 95% confidence interval: 0.26, 1.68). In this setting, analytic strategies using EPS or disease risk scores were not generally superior to "conventional" models. Various ways to use EPS and disease risk scores behaved differently with smaller study size

A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods

Objective: Propensity score (PS) analyses attempt to control for confounding in nonexperimental studies by adjusting for the likelihood that a given patient is exposed. Such analyses have been proposed to address confounding by indication, but there is little empirical evidence that they achieve better control than conventional multivariate outcome modeling. Study Design and Methods: Using PubMed and Science Citation Index, we assessed the use of propensity scores over time and critically evaluated studies published through 2003. Results: Use of propensity scores increased from a total of 8 reports before 1998 to 71 in 2003. Most of the 177 published studies abstracted assessed medications (N = 60) or surgical interventions (N = 51), mainly in cardiology and cardiac surgery (N = 90). Whether PS methods or conventional outcome models were used to control for confounding had little effect on results in those studies in which such comparison was possible. Only 9 of 69 studies (13%) had an effect estimate that differed by more than 20% from that obtained with a conventional outcome model in all PS analyses presented. Conclusions: Publication of results based on propensity score methods has increased dramatically, but there is little evidence that these methods yield substantially different estimates compared with conventional multivariable methods