Pauline Heus

Prediction models for cardiovascular disease risk in the general population: systematic review

Objective To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population. Design Systematic review. Data sources Medline and Embase until June 2013. Eligibility criteria for study selection Studies describing the development or external validation of a multivariable model for predicting CVD risk in the general population. Results 9965 references were screened, of which 212 articles were included in the review, describing the development of 363 prediction models and 473 external validations. Most models were developed in Europe (n=167, 46%), predicted risk of fatal or non-fatal coronary heart disease (n=118, 33%) over a 10 year period (n=209, 58%). The most common predictors were smoking (n=325, 90%) and age (n=321, 88%), and most models were sex specific (n=250, 69%). Substantial heterogeneity in predictor and outcome definitions was observed between models, and important clinical and methodological information were often missing. The prediction horizon was not specified for 49 models (13%), and for 92 (25%) crucial information was missing to enable the model to be used for individual risk prediction. Only 132 developed models (36%) were externally validated and only 70 (19%) by independent investigators. Model performance was heterogeneous and measures such as discrimination and calibration were reported for only 65% and 58% of the external validations, respectively. Conclusions There is an excess of models predicting incident CVD in the general population. The usefulness of most of the models remains unclear owing to methodological shortcomings, incomplete presentation, and lack of external validation and model impact studies. Rather than developing yet another similar CVD risk prediction model, in this era of large datasets, future research should focus on externally validating and comparing head-to-head promising CVD risk models that already exist, on tailoring or even combining these models to local settings, and investigating whether these models can be extended by addition of new predictors.

Improving GRADE evidence tables part 3: detailed guidance for explanatory footnotes supports creating and understanding GRADE certainty in the evidence judgments

BACKGROUND The Grading of Recommendations Assessment, Development and Evaluation (GRADE) is widely used and reliable and accurate for assessing the certainty in the body of health evidence. The GRADE working group has provided detailed guidance for assessing the certainty in the body of evidence in systematic reviews and health technology assessments (HTAs) and how to grade the strength of health recommendations. However, there is limited advice regarding how to maximize transparency of these judgments, in particular through explanatory footnotes or explanations in Summary of Findings tables and Evidence Profiles (GRADE evidence tables). METHODS We conducted this study to define the essential attributes of useful explanations and to develop specific guidance for explanations associated with GRADE evidence tables. We used a sample of explanations according to their complexity, type of judgment involved, and appropriateness from a database of published GRADE evidence tables in Cochrane reviews and World Health Organization guidelines. We used an iterative process and group consensus to determine the attributes and develop guidance. RESULTS Explanations in GRADE evidence tables should be concise, informative, relevant, easy to understand, and accurate. We provide general and domain-specific guidance to assist authors with achieving these desirable attributes in their explanations associated with GRADE evidence tables. CONCLUSIONS Adhering to the general and GRADE domain-specific guidance should improve the quality of explanations associated with GRADE evidence tables, assist authors of systematic reviews, HTA reports, or guidelines with information that they can use in other parts of their evidence synthesis. This guidance will also support editorial evaluation of evidence syntheses using GRADE and provide a minimum quality standard of judgments across tables.

Improving GRADE evidence tables part 2: a systematic survey of explanatory notes shows more guidance is needed

OBJECTIVES The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group has developed GRADE evidence profiles (EP) and summary of findings (SoF) tables to present evidence summaries in systematic reviews, clinical guidelines, and health technology assessments. Explanatory notes are used to explain choices and judgments in these summaries, for example, on rating of the quality of evidence. STUDY DESIGN AND SETTING A systematic survey of the explanations in SoF tables in 132 randomly selected Cochrane Intervention reviews and in EPs of 10 guidelines. We analyzed the content of 1,291 explanations using a predefined list of criteria. RESULTS Most explanations were used to describe or communicate results and to explain downgrading of the quality of evidence, in particular for risk of bias and imprecision. Addressing the source of baseline risk (observational data or control group risk) was often missing. For judgments about downgrading the quality of evidence, the percentage of informative explanations ranged between 41% (imprecision) and 79% (indirectness). CONCLUSION We found that by and large explanations were informative but detected several areas for improvement (e.g., source of baseline risk and judgments on imprecision). Guidance about explanatory footnotes and comments will be provided in the last article in this series.

Een meting van het substitutiepotentieel binnen de oogzorg.

Met de toenemende zorgvraag en stijgende zorgkosten is ook taakherschikking binnen de oogzorg in Nederland een thema geworden. Er bestaat echter nauwelijks onderzoek naar de taakverdeling binnen de eerstelijns oogzorg, en meer specifiek wat de rol van de eerstelijns optometrist hierin zou kunnen zijn. In dit artikel is met behulp van patiënten-data van huisartsen en optometristen het substitutiepotentieel van de optometrist geschat voor een aantal aandoeningen die door enkele oogartsen en optometristen als ‘substitueerbaar’ zijn beoordeeld. Hieruit blijkt dat de optometrist jaarlijks potentieel 207.000 patiënten zou kunnen opvangen die anders door huisartsen geconsulteerd zouden zijn. De optometrist kan eveneens patiënten onderzoeken en adviseren die via de huisarts veelal naar de duurdere tweedelijns oogarts worden verwezen. Het kan hierbij in theorie om potentieel 21.000 patiënten gaan. De resultaten van dit onderzoek moeten vooralsnog met grote voorzichtigheid worden geïnterpreteerd. Zo is onder meer alleen een beperkte lijst van substitueerbare oogaandoeningen, door een beperkt aantal experts, beoordeeld. Daarnaast waren de aandoeningen-classificaties uit de gebruikte datasets vaak niet vergelijkbaar. Gegeven deze beperkingen, levert dit onderzoek een bijdrage aan de schatting hoe de optometrist in Nederland potentieel substitutie binnen de oogzorg kan bewerkstelligen.Attention to the optometrist. A measurement of the substitution potential within Dutch eye careIn recent years tasks reallocation between professions within Dutch eye care has been gaining importance in health policy, due to a higher demand for medical care and increasing financial costs. Empirical research focusing on the (potential) role of optometrists concerning task substitution barely exists, however. The aim of this study is to indicate the ‘substitution potential’ of optometrists within the eye care system. Based on patient-data of optometrists and general practitioners we estimated the substitution potential for a number of eye diseases. These diseases were judged as ‘substitutable’ according to two ophthalmologists and four optometrists. Results show that an annual shift of up to 207,000 general practitioner patients to the optometrist is possible, and up to 21,000 ophthalmologist patients can be prevented in case general practitioners refer patients with eye problems to the optometrist instead of the ophthalmologist. Our analysis estimated the potential pivotal volume taking by optometrists through task substitution within Dutch eye care. Results need to be interpreted carefully, however. A number of limitations have to be taken into account: (1) the list of potential substitutable’ eye diseases was assessed by only six experts, and (2) statistics on a limited number of eye diseases were available or comparable in datasets of general practice and optometrist practices. This study primarily provides a conceptual method to explore what volumes optometrists can attribute to task substitution within the Dutch eye care system.