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Table 1 Study characteristics of prognostic model studies using flexible parametric survival models

From: The current application of the Royston-Parmar model for prognostic modeling in health research: a scoping review

Author (year)

Country

Topic area of research

Data source

Study setting

Sample size

Maximum follow-up time

Timescale

Event/outcome

Number of events

Andersson et al. (2014) [34]

Sweden

Cancer

Administrative data

Country

5850

15 years

Calendar time

Mortality

1951

Baade et al. (2015) [33]

Australia

Cancer

Administrative data

Country

870,878

21 years

Calendar time

Mortality

261,720

Baade et al. (2015) [41]

Australia

Cancer

Administrative data

Secondary care

28,654

16 years

Calendar time

Mortality

5469

Castillo et al. (2013) [38]

United States of America

Cancer

Administrative data

Primary care

2284

12 years

Calendar time

Mortality

1210

Csordas et al. (2016) [37]

Switzerland

Cardiovascular

Clinical data

Hospital

185

222 days

Calendar time

Mortality

17

Eyre et al. (2012) [40]

United Kingdom

Infectious disease

Administrative data

Hospital

1678

4.6 years

Calendar time

Clostridium difficile infection recurrence

363

Fox et al. (2014) [32]

United Kingdom

Cancer

Clinical data

Hospital

2918

Not stated

Calendar time

Mortality

Not stated

Li et al. (2016) [39]

United Kingdom

Organ transplant

Administrative data

Secondary care

12,307

10 years

Calendar time

Mortality

1503

Miladinovic et al. (2012) [30]

United States of America

Aging

Medical records

Hospice

590

371 days

Calendar time

Mortality

590

Myklebust et al.(2016) [31]

Norway

Cancer

Administrative data

Country

805,365

15 years

Calendar time

Mortality

Not stated

Ramezani Tehrani et al. (2016) [35]

Iran

Reproductive/perinatal

Population survey

Community

1015

12.3 years

Age

Menopause

277

Sanchis et al. (2014) [36]

Spain

Cardiovascular

Clinical data

Hospital

342

34 months

Calendar time

Mortality

74