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2020-4231

Research Proposal

Project Title: 
A systematic review and individual patient data meta-analysis of blood biomarkers in idiopathic pulmonary fibrosis
Scientific Abstract: 

Background: Idiopathic Pulmonary Fibrosis (IPF) is a devastating lung condition of unknown origin, characterised by variable and unpredictable disease behaviour. A number of studies evaluating the role of blood biomarkers in predicting progression have been published.

Objectives: We aim to conduct a systematic review and meta-analysis of individual patient data of treatment naive IPF patients to assess whether baseline and/or short term change in matrix metalloproteinase-7 (MMP7) can accurately predict important clinical outcomes such as disease progression and mortality.

Study Design: Individual patient data from observational studies will be analysed, and a two-step meta-analysis performed.

Participants: Adult patients with untreated IPF evaluated in prospective observational studies.

Main outcome measures: Mortality and disease progression (defined as relative decline in forced vital capacity of at least 10%, or death, at 12 months)

Statistical analysis: Individual patient data will be sought and a two-step meta-analysis performed adjusted for a priori confounders including age, sex and smoking status. Hazard ratios for baseline and three month change of MMP-7 in predicting mortality will be calculated. Disease progression will be standardised as 10% relative decline in forced vital capacity (FVC) or death within 12 months of baseline, and odds ratios for predicting disease progression calculated.

Brief Project Background and Statement of Project Significance: 

Idiopathic pulmonary fibrosis (IPF) is a devastating lung condition of unknown origin characterised by progressive and irreversible interstitial fibrosis. Although median survival is 3 years, IPF is manifest by variable and unpredictable disease trajectory amongst individual patients. Advances in the management of IPF are hampered by the absence of validated prognostic measures, especially biomarkers that change over short time periods. Biomarkers, both serum and physiological may be suitable as early predictive markers of disease behaviour enabling stratification of therapy and personalised medicine. We aim to conduct a systematic review and if possible, meta-analysis, to critically appraise existing evidence and evaluate the usefulness of serum and physiological biomarkers as prognostic factors for IPF. A scoping search of the Database of Abstracts of Reviews of Effects (DARE) did not identify any current or past reviews regarding the research question.

Following initial searches, most data exists for MMP-7 and we wish to explore the role of this biomarker in predicting mortality and disease progression, using individual patient data meta-analysis.

Specific Aims of the Project: 

To identify whether baseline serum MMP-7 or subsequent change over 3 months predict prognosis in untreated patients with idiopathic pulmonary fibrosis.

What is the purpose of the analysis being proposed? Please select all that apply.: 
Participant-level data meta-analysis
Participant-level data meta-analysis pooling data from YODA Project with other additional data sources
Software Used: 
STATA
Data Source and Inclusion/Exclusion Criteria to be used to define the patient sample for your study: 

Types of study to be included
Inclusion: All original prospective observational studies that report outcomes from adult (aged > 18) patients with IPF stratified according to status of at least one biomarker. Conference abstracts and placebo arms of randomised interventional clinical trials will also be eligible for inclusion.

Exclusion: Letters, commentaries, correspondence, case reports, expert opinions, editorials, other non-original systematic reviews, retrospective studies, experimental studies and animal studies. Studies investigating non-IPF Interstitial Lung Diseases.

Participants/population
Adult patients aged > 18 with idiopathic pulmonary fibrosis diagnosed according to contemporaneous consensus guidelines.

Details of other studies to be included (PMID) and their data source:

PMID: 27761978 - Corresponding author
PMID: 22016448 - Corresponding author
PMID: 29150411 - Corresponding author
PMID: 30072107 - CSDR
PMID: 29100885 - Corresponding author
PMID: 30526970 - CSDR
PMID: 27293304 - Corresponding author

Main Outcome Measure and how it will be categorized/defined for your study: 

Main outcome(s)
Overall mortality (all-cause)

Additional outcome(s)
1) Absolute or relative percentage change from baseline in forced vital capacity (FVC) at 12 months
2) Disease progression at 12 months defined as:
a. >10% relative decline in FVC
b. Death

Main Predictor/Independent Variable and how it will be categorized/defined for your study: 

Baseline MMP-7 and change in MMP-7 over 3 months

Other Variables of Interest that will be used in your analysis and how they will be categorized/defined for your study: 

Age
Gender
Smoker (Ever or never)

Statistical Analysis Plan: 

A narrative synthesis of the findings from the included studies will be presented with summary tables for study characteristics and quality assessment. Data will be aggregated, and meta-analysis conducted if there is adequate data for analysis. The I² test of heterogeneity and visual inspections of forest plots will be used to measure heterogeneity between studies. The thresholds for interpretation of I² will be in accordance with the definitions presented in the Cochrane Handbook for Systematic Reviews of Interventions.

Only studies that provide a survival estimate of the hazard ratio (HR) and associated 95% confidence interval (CI) for each biomarker, or sufficient information to enable calculation of these values using the inverse variance method will be used in the meta-analyses of overall survival. Adjusted HRs will be used where possible, and sensitivity analysis excluding unadjusted HRs carried out to confirm that findings are robust. Summary-estimates for the HR will be computed by the random-effects model.

Sample sizes, mean values and standard deviations of the biomarkers for individuals with and without disease progression will be extracted where possible to enable calculation of the standardised mean difference (SMD). Measurements of relative risk (including hazard ratios, odds ratios and risk ratios) will also be reported where appropriate.

Continuous outcome data (change in FVC at 12 months) will be combined using either correlation coefficients with meta-regression or standardised mean differences. Trend data will be analysed using ANOVA. Studies that report correlation coefficients for biomarker (baseline and trend) association with change in lung function will be reported in a narrative manner if there are insufficient data for meta-analysis. ROC analysis will be carried out to compare baseline values or three-month change with twelve-month change in predicting outcomes. Positive predictive values from the included samples will be calculated through contingency tables.

Specifically for MMP-7 data, hazard ratios for predicting mortality will be estimated using a two-step individual patient data meta-analysis with random effects, and adjusted for a priori confounders including age, gender, smoking and baseline FVC. Disease progression will be defined as relative FVC decline of >10% or death within 12 months of baseline. Odds ratio's will be calculated for MMP-7 in predicting disease progression.

Data from YODA studies will be analysed using the secure platform, and summary level data exported and combined with summary level data from other studies. No individual patient data will be downloaded.

Narrative Summary: 

Idiopathic pulmonary fibrosis (IPF) is a devastating lung condition of unknown origin characterised by progressive and irreversible interstitial fibrosis. Although median survival is 3 years, IPF is manifest by variable and unpredictable disease trajectory amongst individual patients. Blood biomarkers may be suitable as early predictive markers of disease behaviour enabling stratification of therapy and personalised medicine. Following an initial search, there appears to be most data for MMP-7 (matrix metalloproteinase 7), so we hope to synthesise the data around this biomarker and perform an individual patient data meta-analysis to explore the usefulness of this biomarker in IPF.

Project Timeline: 

Review started.

Analysis completion date - 1st May 2020
Manuscript submitted - 1st June 2020
Results reported back to YODA - 1st June 2020

Dissemination Plan: 

All data will be anonymised and grouped for presentation and publication. The results from this study will be publicised at regional and national conferences as well as being submitted for publication in open access peer-reviewed journals in accordance with UK Research Council policies. No participants will be identified in any publications that arise from this research.

Conferences to be presented at - British Thoracic Society Winter Meeting, European Respiratory Society Meeting
Journals to be submitted to - Thorax

Bibliography: 

1. Navaratnam V, Fleming KM, West J, et al. The rising incidence of idiopathic pulmonary fibrosis in the U.K. Thorax 2011;66(6):462-7. doi: 10.1136/thx.2010.148031
2. Raghu G, Weycker D, Edelsberg J, et al. Incidence and prevalence of idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2006;174(7):810-6. doi: 10.1164/rccm.200602-163OC [published Online First: 2006/07/01]
3. Lederer DJ, Martinez FJ. Idiopathic Pulmonary Fibrosis. N Engl J Med 2018;378(19):1811-23. doi: 10.1056/NEJMra1705751 [published Online First: 2018/05/10]
4. Navaratnam V, Hubbard RB. The Mortality Burden of Idiopathic Pulmonary Fibrosis in the United Kingdom. Am J Respir Crit Care Med 2019 doi: 10.1164/rccm.201902-0467LE [published Online First: 2019/04/12]
5. Martinez FJ, Collard HR, Pardo A, et al. Idiopathic pulmonary fibrosis. Nat Rev Dis Primers 2017;3:17074. doi: 10.1038/nrdp.2017.74 [published Online First: 2017/10/21]
6. Ley B, Collard HR, King TE, Jr. Clinical course and prediction of survival in idiopathic pulmonary fibrosis. American journal of respiratory and critical care medicine 2011;183(4):431-40. doi: 10.1164/rccm.201006-0894CI [published Online First: 2010/10/12]

Supplementary Material: 

General Information

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What type of data are you looking for?: 
Individual Participant-Level Data, which includes Full CSR and all supporting documentation

Data Request Status

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