Overview of data-synthesis in systematic reviews of studies on outcome prediction models.

BACKGROUND: Many prognostic models have been developed. Different types of models, i.e. prognostic factor and outcome prediction studies, serve different purposes, which should be reflected in how the results are summarized in reviews. Therefore we set out to investigate how authors of reviews synthesize and report the results of primary outcome prediction studies. METHODS: Outcome prediction reviews published in MEDLINE between October 2005 and March 2011 were eligible and 127 Systematic reviews with the aim to summarize outcome prediction studies written in English were identified for inclusion.Characteristics of the reviews and the primary studies that were included were independently assessed by 2 review authors, using standardized forms. RESULTS: After consensus meetings a total of 50 systematic reviews that met the inclusion criteria were included. The type of primary studies included (prognostic factor or outcome prediction) was unclear in two-thirds of the reviews. A minority of the reviews reported univariable or multivariable point estimates and measures of dispersion from the primary studies. Moreover, the variables considered for outcome prediction model development were often not reported, or were unclear. In most reviews there was no information about model performance. Quantitative analysis was performed in 10 reviews, and 49 reviews assessed the primary studies qualitatively. In both analyses types a range of different methods was used to present the results of the outcome prediction studies. CONCLUSIONS: Different methods are applied to synthesize primary study results but quantitative analysis is rarely performed. The description of its objectives and of the primary studies is suboptimal and performance parameters of the outcome prediction models are rarely mentioned. The poor reporting and the wide variety of data synthesis strategies are prone to influence the conclusions of outcome prediction reviews. Therefore, there is much room for improvement in reviews of outcome prediction studies.

Diagnostic value of patient characteristics, history, and six clinical tests for traumatic anterior shoulder instability.

BACKGROUND: It is unknown which combination of patient information and clinical tests might be optimal for the diagnosis of traumatic anterior shoulder instability. This study aimed to determine the diagnostic value of individual clinical tests and to develop a prediction model that combined patient characteristics, history, and clinical tests for diagnosis of traumatic anterior shoulder instability. MATERIALS AND METHODS: This prospective cohort study included 169 consecutive patients with shoulder complaints who were examined at an orthopaedic outpatient clinic. One experienced clinician conducted 25 clinical tests; of these, 6 were considered to be specific for testing of traumatic anterior shoulder instability (apprehension, relocation, release, anterior drawer, load and shift, and hyperabduction tests). Magnetic resonance arthrography was used to determine the final diagnosis. A prediction model was developed by logistic regression analysis. RESULTS: In this cohort, 60 patients (36%) were diagnosed with anterior shoulder instability on the basis of magnetic resonance arthrography. The overall accuracy of individual clinical tests was 80.5% to 86.4%. Age, previous shoulder dislocation, sudden onset of complaints, and the release test were important predictors for the diagnosis of traumatic anterior shoulder instability. The prediction model demonstrated high discriminative ability (AUC 0.95). CONCLUSION: Individual clinical shoulder tests provide good diagnostic accuracy. Young age, history of shoulder dislocation, sudden onset of complaints, and positive result of the release test were the most important predictors for traumatic anterior shoulder instability.

Systematic review: do patient expectations influence treatment outcomes in total knee and total hip arthroplasty?

OBJECTIVE: This systematic review aims to summarise all the available evidence related to the association between pre-operative patient expectations (outcome expectations, process expectations and self efficacy expectations) and 5 different treatment outcomes (overall improvement, pain, function, stiffness and satisfaction) in patients with total knee or total hip arthroplasty at three different follow-op periods (>6 weeks; >6 weeks- ≤6 months; >6 months). METHODS: English and Dutch language articles were identified through PubMed, EMBASE.com, PsycINFO, CINAHL and The Cochrane Library from inception to September 2012. Articles assessing the association between pre-operative patient expectations and treatment outcomes for TKA/THA in either adjusted or unadjusted analysis were included. Two reviewers, working independently, determined eligibility, rated methodological quality and extracted data on study design, population, expectation measurements, outcome measurements and strength of the associations. Methodological quality was rated by the same reviewers on a 19 item scale. The scores on the quality assessment were taken into account when drawing final conclusions. RESULTS: The search strategy generated 2252 unique references, 18 articles met inclusion criteria. Scores on the methodological quality assessment ranged between 6% and 79%. Great variety was seen in definitions and measurement methods of expectations. No significant associations were found between patient expectations and overall improvement, satisfaction and stiffness. Both significant positive and non-significant associations were found for the association between expectations and pain and function. CONCLUSIONS: There was no consistency in the association between patients' pre-operative expectations and treatment outcomes for TKA and THA indentified in this systematic review. There exists a need for a sound theoretical framework underlying the construct of 'patient expectations' and consistent use of valid measurement instruments to measure that construct in order to facilitate future research synthesis.

The diagnostic value of the combination of patient characteristics, history, and clinical shoulder tests for the diagnosis of rotator cuff tear.

BACKGROUND: It is unknown which combination of patient information and clinical tests might be optimal for the diagnosis of rotator cuff tears. This study aimed to determine the diagnostic value of nine individual clinical tests for evaluating rotator cuff tear and to develop a prediction model for diagnosing rotator cuff tear. METHODS: This prospective cohort study included 169 patients with shoulder complaints. Patients who reported a previous shoulder dislocation were excluded from the analysis (N = 69). One experienced clinician conducted 25 clinical tests of which 9 are specifically designed to diagnose rotator cuff pathology (empty can, Neer, Hawkins-Kenney, drop arm, lift-off test, painful arc, external rotation lag sign, drop sign, infraspinatus muscle strength test). The final diagnosis, based on magnetic resonance arthrography (MRA), was determined by consensus between the clinician and a radiologist, who were blinded to patient information. A prediction model was developed by logistic regression analysis. RESULTS AND DISCUSSION: In this cohort, 38 patients were diagnosed with rotator cuff tears. The individual overall accuracy of the rotator cuff clinical tests was 61%-75%. After backward selection, the model determined that the most important predictors of rotator cuff tears were higher age and a positive Neer test. This internally validated prediction model had good discriminative ability (area under the receiver operating characteristic curve (AUC) = 0.73). CONCLUSION: Our results showed that individual clinical shoulder tests had moderate diagnostic value for diagnosing rotator cuff tear. Our prediction model showed improved diagnostic value. However, the prediction value is still relatively low, supporting a low threshold for additional diagnostic tests for the diagnosis of rotator cuff tears. LEVEL OF EVIDENCE: Study of diagnostic test: level I.

Methodology of clinical nutrition guidelines for adult cancer patients: how good are they according to AGREE criteria?

BACKGROUND: Malnutrition delays recovery from cancer treatment and can lead to additional serious complications. Clinical guidelines for the management of malnutrition in cancer patients are essential tools for optimizing nutritional care; therefore, their methodological quality is of great importance. This review assesses the methodological quality of international clinical guidelines for the management of malnutrition in adult cancer patients. METHODS: Guidelines were identified through searches in multiple electronic databases; afterward, they were systematically reviewed with the AGREE instrument, which is one method of evaluating the methodological quality of guidelines. RESULTS: The methodological quality of the guidelines reviewed varied greatly. The highest scores were observed in the domains "scope and purpose" and "clarity and presentation," while the lowest scores were awarded in the domains "editorial independence," "stakeholder involvement," and "applicability." Furthermore, there was consensus on the indication for parenteral nutrition and nutrition screening. However, there was a lack of consensus on how nutritional therapy should be provided. No improvement was observed in methodological quality of the more recent guidelines compared to the older ones. CONCLUSIONS: The methodological quality of clinical guidelines on malnutrition for cancer patients and the way they are reported need to be improved. To achieve this, developers should utilize available guideline assessment tools, such as the AGREE instrument, when writing or updating guidelines on this topic.

Preliminary state of development of prediction models for primary care physical therapy: a systematic review.

OBJECTIVE: To summarize the methodological quality and developmental stage of prediction models for musculoskeletal complaints that are relevant for physical therapists in primary care. STUDY DESIGN AND SETTING: A systematic literature search was carried out in the databases of Medline, Embase, and Cinahl. Studies on prediction models for musculoskeletal complaints that can be used by primary care physical therapists were included. Methodological quality of the studies was assessed and relevant study characteristics were extracted. RESULTS: The search retrieved 4,702 references of which 29 studies were included in this review. The study quality of the included studies showed substantial variation. The studied populations consisted mostly of back (n=10) and neck pain (n=6) patients, and patients with knee complaints (n=4). Most studies (n=22) used "perceived recovery" as primary outcome. Most prediction models (n=18) were at the derivation level of development. CONCLUSIONS: Many prediction models are available for a wide range of patient populations. The developmental stage of most models is preliminary and the study quality is often moderate. We do not recommend physiotherapist to use these models yet. All models reviewed here are in the developmental stage and need validation and impact evaluation before using them in daily practice.