Literature DB >> 18471659

Identifying phases of investigation helps planning, appraising, and applying the results of explanatory prognosis studies.

J A Hayden1, P Côté, I A Steenstra, C Bombardier.   

Abstract

OBJECTIVE: To present an explanatory framework for understanding prognosis and illustrate it using data from a systematic review. STUDY DESIGN AND
SETTING: A framework including three phases of explanatory prognosis investigation was adapted from earlier work and a discussion of causal understanding was integrated. For illustration, prognosis studies were identified from electronic and supplemental searches of literature between 1966 and December 2006. We extracted characteristics of the populations, exposures, and outcomes and identified three phases of explanatory prognosis investigation: Phase 1, identifying associations; Phase 2, testing independent associations; and Phase 3, understanding prognostic pathways. The purpose of each phase is exploration, confirmation, and development of understanding, respectively.
RESULTS: It is important to consider a framework of explanatory prognosis studies for: (1) defining the study objectives, (2) presenting the study methods and data, and (3) interpreting and applying the results of the study.
CONCLUSION: When conducting and reporting prognosis studies, researchers should consider the approach to prognosis (explanatory or outcome prediction) and phase of investigation, use best methods to limit biases, report completely, and cautiously interpret results. Readers of health care research will then be better able to evaluate the goals and interpret and appropriately use the results of prognosis studies.

Mesh:

Year:  2008        PMID: 18471659     DOI: 10.1016/j.jclinepi.2007.08.005

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  39 in total

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Authors:  Jill A Hayden; Maria N Wilson; Richard D Riley; Ross Iles; Tamar Pincus; Rachel Ogilvie
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Review 2.  Incremental predictive value of natriuretic peptides for prognosis in the chronic stable heart failure population: a systematic review.

Authors:  Andrew C Don-Wauchope; Pasqualina L Santaguida; Mark Oremus; Robert McKelvie; Usman Ali; Judy A Brown; Amy Bustamam; Nazmul Sohel; Stephen A Hill; Ronald A Booth; Cynthia Balion; Parminder Raina
Journal:  Heart Fail Rev       Date:  2014-08       Impact factor: 4.214

3.  Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

Authors:  Stefan Bösner; Jörg Haasenritter; Annette Becker; Konstantinos Karatolios; Paul Vaucher; Baris Gencer; Lilli Herzig; Monika Heinzel-Gutenbrunner; Juergen R Schaefer; Maren Abu Hani; Heidi Keller; Andreas C Sönnichsen; Erika Baum; Norbert Donner-Banzhoff
Journal:  CMAJ       Date:  2010-07-05       Impact factor: 8.262

Review 4.  Evaluating the quality of research into a single prognostic biomarker: a systematic review and meta-analysis of 83 studies of C-reactive protein in stable coronary artery disease.

Authors:  Harry Hemingway; Peter Philipson; Ruoling Chen; Natalie K Fitzpatrick; Jacqueline Damant; Martin Shipley; Keith R Abrams; Santiago Moreno; Kate S L McAllister; Stephen Palmer; Juan Carlos Kaski; Adam D Timmis; Aroon D Hingorani
Journal:  PLoS Med       Date:  2010-06-01       Impact factor: 11.069

5.  Research methods for subgrouping low back pain.

Authors:  Peter Kent; Jennifer L Keating; Charlotte Leboeuf-Yde
Journal:  BMC Med Res Methodol       Date:  2010-07-03       Impact factor: 4.615

6.  Performance of Gene Expression Profile Tests for Prognosis in Patients With Localized Cutaneous Melanoma: A Systematic Review and Meta-analysis.

Authors:  Michael A Marchetti; Daniel G Coit; Stephen W Dusza; Ashley Yu; LaToya McLean; Yinin Hu; Japbani K Nanda; Konstantina Matsoukas; Silvia E Mancebo; Edmund K Bartlett
Journal:  JAMA Dermatol       Date:  2020-09-01       Impact factor: 10.282

7.  Association between Functional Performance and Return to Performance in High-Impact Sports after Lower Extremity Injury: A Systematic Review.

Authors:  Astrid Vereijken; Inne Aerts; Jorrit Jetten; Bruno Tassignon; Jo Verschueren; Romain Meeusen; Emiel van Trijffel
Journal:  J Sports Sci Med       Date:  2020-08-13       Impact factor: 2.988

Review 8.  Prognostic factors for morbidity and mortality in elderly patients undergoing acute gastrointestinal surgery: a systematic review.

Authors:  Philip Davis; Jill Hayden; Jeremy Springer; Jonathon Bailey; Michele Molinari; Paul Johnson
Journal:  Can J Surg       Date:  2014-04       Impact factor: 2.089

9.  Limited predictive value of illness perceptions for short-term poor recovery in musculoskeletal pain. A multi-center longitudinal study.

Authors:  E J de Raaij; H Wittink; J F Maissan; P Westers; R W J G Ostelo
Journal:  BMC Musculoskelet Disord       Date:  2021-06-07       Impact factor: 2.362

10.  Prognostic implications of the Quebec Task Force classification of back-related leg pain: an analysis of longitudinal routine clinical data.

Authors:  Alice Kongsted; Peter Kent; Tue Secher Jensen; Hanne Albert; Claus Manniche
Journal:  BMC Musculoskelet Disord       Date:  2013-05-24       Impact factor: 2.362

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