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Table 1 Characteristics of identified studies

From: Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis

 

N (%)

Full text or abstract available

 Full text

63 (96.9)

 Abstract

2 (3.1)

Disease Area

 Cancer related data

10 (15.4)

 HIV/AIDS

9 (13.8)

 Patient status after transplants

8 (12.3)

 Cognitive decline

7 (10.8)

 Glaucoma

4 (6.2)

 Renal disease

4 (6.2)

 Disability in the elderly

3 (4.6)

 Heart related data

3 (4.6)

 Schizophrenia

3 (4.6)

 Sclerosis

3 (4.6)

 Other

11 (16.9)

Journal

 Statistics in Medicine

5 (7.7)

 Journal of the Royal Statistical Society. Series C: Applied Statistics

4 (6.2)

 Ophthalmology

3 (4.6)

 Quality of Life Research

3 (4.6)

 Journal of the American Geriatrics Society

2 (3.1)

 Journal of the American Statistical Association

2 (3.1)

 Journals of Gerontology - Series B Psychological Sciences and Social Sciences

2 (3.1)

 Statistical Methods in Medical Research

2 (3.1)

 Other (only one study per journal)

45 (64.6)

Reason for joint modelling use*

 To investigate the link between longitudinal and time-to-event outcomes

43 (66.2)

 To account for dropout

22 (33.8)

 To include longitudinally measured variable in time-to-event model

4 (6.2)

 To increase efficiency

3 (4.6)

 To reduce bias

2 (3.1)

 Easier to interpret

1 (1.5)

 To use of all available data

1 (1.5)

  1. *Note for “disease area” and “journal” only one value was recorded per included study giving total N = 65, however for “reason for joint modelling use” multiple reasons could be recorded per included study giving total N ≥ 65