Michael J DeVivo1, Gordana Savic2, Hans L Frankel3, Mohamed Ali Jamous3, Bakulesh M Soni4, Susan Charlifue5, James W Middleton6, John Walsh7. 1. University of Alabama at Birmingham, Birmingham, Alabama, USA. 2. National Spinal Injuries Centre, Stoke Mandeville Hospital, Buckinghamshire Healthcare NHS Trust, Aylesbury, UK. Gordana.Savic@buckshealthcare.nhs.uk. 3. National Spinal Injuries Centre, Stoke Mandeville Hospital, Buckinghamshire Healthcare NHS Trust, Aylesbury, UK. 4. North West Regional Spinal Injuries Centre, Southport Hospital, Southport and Ormskirk NHS Trust, Southport, UK. 5. Craig Hospital, Englewood, Colorado, USA. 6. Rehabilitation Studies Unit, The University of Sydney, NSW State Spinal Cord Injury Service, Agency for Clinical Innovation, Sydney, Australia. 7. John Walsh Centre for Rehabilitation Research, The University of Sydney, Sydney, Australia.
Abstract
STUDY DESIGN: Retrospective observational. OBJECTIVES: To compare results of several different methods for calculating life expectancy in the same sample of people with spinal cord injury (SCI), and critically assess their advantages and disadvantages. SETTING: Two spinal centres in Great Britain. METHODS: Survival status of persons with traumatic SCI injured between 1943 and 2010 with follow-up to 2015 was determined. Standardised mortality ratios (SMRs) were calculated using age at injury and current (attained) age, and compared. Life expectancy was then estimated using the SMR methods and compared with the results of a method based on multivariate logistic regression of a person-year dataset. Life expectancy estimates calculated by applying SMRs based on current age to general population period (current) and cohort (projected) life tables were also compared. RESULTS: The estimated life expectancies were significantly higher when the SMRs were based on age at injury. They were also higher when a general population cohort life table was used, particularly for younger ages. With the exception of the ventilator-dependent group, the life expectancy estimates derived from logistic regression were slightly lower than those derived from SMRs based on current age and a general population period life table. CONCLUSIONS: The multivariate logistic regression of person-years method offers several advantages compared to the SMR method for calculating life expectancy after SCI, the main ones being: greater statistical power and precision with smaller sample sizes, the ability to include more predictive factors and to distinguish the otherwise confounded effects of current age, time post-injury, and calendar time.
STUDY DESIGN: Retrospective observational. OBJECTIVES: To compare results of several different methods for calculating life expectancy in the same sample of people with spinal cord injury (SCI), and critically assess their advantages and disadvantages. SETTING: Two spinal centres in Great Britain. METHODS: Survival status of persons with traumatic SCI injured between 1943 and 2010 with follow-up to 2015 was determined. Standardised mortality ratios (SMRs) were calculated using age at injury and current (attained) age, and compared. Life expectancy was then estimated using the SMR methods and compared with the results of a method based on multivariate logistic regression of a person-year dataset. Life expectancy estimates calculated by applying SMRs based on current age to general population period (current) and cohort (projected) life tables were also compared. RESULTS: The estimated life expectancies were significantly higher when the SMRs were based on age at injury. They were also higher when a general population cohort life table was used, particularly for younger ages. With the exception of the ventilator-dependent group, the life expectancy estimates derived from logistic regression were slightly lower than those derived from SMRs based on current age and a general population period life table. CONCLUSIONS: The multivariate logistic regression of person-years method offers several advantages compared to the SMR method for calculating life expectancy after SCI, the main ones being: greater statistical power and precision with smaller sample sizes, the ability to include more predictive factors and to distinguish the otherwise confounded effects of current age, time post-injury, and calendar time.
Authors: Robert M Shavelle; Michael J DeVivo; David J Strauss; David R Paculdo; Daniel P Lammertse; Steven M Day Journal: J Spinal Cord Med Date: 2006 Impact factor: 1.985
Authors: Robert M Shavelle; Michael J Devivo; David R Paculdo; Lawrence C Vogel; David J Strauss Journal: J Spinal Cord Med Date: 2007 Impact factor: 1.985
Authors: Eleni M Patsakos; Mark T Bayley; Ailene Kua; Christiana Cheng; Janice Eng; Chester Ho; Vanessa K Noonan; Matthew Querée; B Catharine Craven Journal: J Spinal Cord Med Date: 2021 Impact factor: 1.985