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

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Abstract

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.

Introduction

What is new?

  • 1.

    The developmental stage of most prediction models is preliminary.

  • 2.

    The study quality of the studies in which prediction models were derived showed substantial variation.

  • 3.

    This review provides a clear overview of the current position of prediction models and insight into the shortcomings of these models.

  • 4.

    The results of this study show that present prediction models are not ready to be applied in daily practice.

  • 5.

    Future research should focus on validating earlier derived prediction models, rather than on developing new ones.

Prognostic research provides insight into various patient characteristics and physical examination results that may predict patient outcome. Therefore, such research can help physical therapists improve their prognostic estimations, and make their clinical decisions more transparent and uniform [1]. However, because of the variability in patients and their health problems, it is difficult to adequately estimate prognosis based on studies evaluating a single predicting variable [2], [3]. In prognostic research, this raises the need to focus on multiple prognostic factors at the same time, which allows us to construct so-called prediction models.

Prediction models can be described as a combination of patient characteristics or test results that increase or decrease the probability of treatment success, or a certain prognosis, or diagnosis [4], [5], [6], [7]. The clustering or combining of predicting variables to guide clinical decisions explains the strength of prediction models because this approach better matches the actual context of health care. Because therapeutic actions often depend on prognostic expectations, reliable estimations on this matter are of importance.

In the past decades, many prediction models have been developed that are relevant for physical therapists. We found four reviews that provide an overview of prediction models for musculoskeletal complaints that are relevant for physical therapists in primary care [8], [9], [10], [11]. One review [10] focused on prediction models that are assistive during the physical therapy management of low back pain. The other three reviews [8], [9], [11] focused on prediction models that aim to assist treatment selection. In addition to treatment selection, estimation of the probability of a certain prognosis is important in the work of physical therapists. Physical therapists use this estimation to decide whether or not a patient should be treated. For example, in case of a favorable prognosis, a physical therapist may decide that a wait and see policy is indicated. However, a comprehensive summary of prediction models to guide physical therapists during their evaluation of patient prognosis for musculoskeletal complaints in general is missing. Therefore, the present review addresses this by 1) summarizing prediction models relevant for physical therapy in primary care, 2) evaluating their methodological quality, and 3) describing their stage of development.

Section snippets

Search strategy

A literature search was carried out (up to February 14, 2011) in the databases of Medline, Embase, and Cinahl. The search strategy was based on a previous derived and validated search strategy [12]. In partnership with a medical librarian, this search strategy was slightly adapted to make it suitable for our study aim. The combination of keywords that were used for Medline, are presented in Appendix A at www.jclinepi.com.

In addition, the reference lists of the identified studies were screened

Search strategy

Our search retrieved 4,702 studies' records of which 29 studies were considered eligible for final inclusion. A “cited by” search revealed that seven validation studies [22], [23], [24], [25], [26], [27], [28] were performed for five prediction models [28], [29], [30], [31], [32]. The search results are shown in Fig. 1.

Study quality

Three reviewers performed the quality assessment of the included studies. Cohen's kappa on item level ranged from −0.11 to 1.00 (median score of 0.55). Negative kappa values were

Main findings

This review aimed to summarize and assess the methodological quality of prognostic prediction models that are relevant for physical therapy in primary care, and to describe their stage of development. The results of this review show that there are many prediction models available for a wide range of patient populations. Unfortunately, the developmental stage of most prediction models is somewhat preliminary and the quality of the studies is often moderate. Of the 29 included prediction models,

Conclusion

The initial purpose of this review was to provide an overview of “ready-to-use” prediction models to assist primary care physical therapists during their prognostication process. Unfortunately, we agree with the earlier performed reviews [8], [9], [10], [11] and conclude that the available prediction models are not yet ready to be applied in clinical practice because of their preliminary stage of development. Nevertheless, this study provides a clear overview of the current position of

Acknowledgments

The Scientific College of Physical Therapy (WCF, The Netherlands) provided financial support for this study.

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