Observational epidemiologic studies provide critical data for the evaluation of the potential effects of environmental, occupational and behavioural exposures on human health. Systematic reviews of these studies play a key role in informing policy and practice. Systematic reviews should incorporate assessments of the risk of bias in results of the included studies. To develop a new tool, Risk Of Bias In Non-randomized Studies - of Exposures (ROBINS-E) to assess risk of bias in estimates from cohort studies of the causal effect of an exposure on an outcome. ROBINS-E was developed by a large group of researchers from diverse research and public health disciplines through a series of working groups, in-person meetings and pilot testing phases. The tool aims to assess the risk of bias in a specific result (exposure effect estimate) from an individual observational study that examines the effect of an exposure on an outcome. A series of preliminary considerations informs the core ROBINS-E assessment, including details of the result being assessed and the causal effect being estimated. The assessment addresses bias within seven domains, through a series of 'signalling questions'. Domain-level judgements about risk of bias are derived from the answers to these questions, then combined to produce an overall risk of bias judgement for the result, together with judgements about the direction of bias. ROBINS-E provides a standardized framework for examining potential biases in results from cohort studies. Future work will produce variants of the tool for other epidemiologic study designs (e.g. case-control studies). We believe that ROBINS-E represents an important development in the integration of exposure assessment, evidence synthesis and causal inference.

Review from JAMA — Cancer Survivors and Unemployment — A Meta-analysis and Meta-regression

A systematic review of qualitative and quantitative studies. To summarize evidence from studies among patients with low back pain on their expectations and satisfaction with treatment as part of practice guideline development. Patients are often dissatisfied with treatment for acute or chronic back pain. We searched the literature for studies on patient expectations and satisfaction with treatment for low back pain. Treatment aspects related to expectations or satisfaction were identified in qualitative studies. Percentages of dissatisfied patients were calculated from quantitative studies. Twelve qualitative and eight quantitative studies were found. Qualitative studies revealed the following aspects that patient expectation from treatment for back pain or with which they are dissatisfied. Patients want a clear diagnosis of the cause of their pain, information and instructions, pain relief, and a physical examination. Next, expectations are that there are more diagnostic tests, other therapy or referrals to specialists, and sickness certification. They expect confirmation from the healthcare provider that their pain is real. Like other patients, they want a confidence-based association that includes understanding, listening, respect, and being included in decision-making. The results from qualitative studies are confirmed by quantitative studies. Patients have explicit expectations on diagnosis, instructions, and interpersonal management. New strategies need to be developed in order to meet patients’ expectations better. Practice guidelines should pay more attention to the best way of discussing the causes and diagnosis with the patient and should involve them in the decision-making process.

The objective of this paper is to explain how to apply, interpret, and present the results of a new instrument to assess the risk of bias (RoB) in non-randomized studies (NRS) dealing with effects of environmental exposures on health outcomes. This instrument is modeled on the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) instrument. The RoB instrument for NRS of exposures assesses RoB along a standardized comparison to a randomized target experiment, instead of the study-design directed RoB approach. We provide specific guidance for the integral steps of developing a research question and target experiment, distinguishing issues of indirectness from RoB, making individual-study judgments, and performing and interpreting sensitivity analyses for RoB judgments across a body of evidence. Also, we present an approach for integrating the RoB assessments within the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework to assess the certainty of the evidence in the systematic review. Finally, we guide the reader through an overall assessment to support the rating of all domains that determine the certainty of a body of evidence using the GRADE approach.