Relative mortality and survival in multiple sclerosis: findings from British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: To examine mortality and factors associated with survival in a population based multiple sclerosis (MS) cohort. METHODS: Clinical and demographic data of MS patients registered with the British Columbia MS clinics (1980-2004) were linked to provincial death data, and patients were followed until death, emigration or study end (31 December 2007). Absolute survival and the influence of patient characteristics (sex, disease course (primary progressive (PPMS) vs relapsing onset (R-MS)) and onset age) were estimated by Kaplan-Meier analyses (from birth and disease onset). Mortality relative to the general population was examined using standardised mortality ratios. Excess mortality associated with patient characteristics and time period of cohort entry was assessed by relative survival modelling. RESULTS: Of 6917 patients, 1025 died. Median survival age was 78.6 years (95% CI 77.5 to 79.7) for women and 74.3 years (95% CI 73.1 to 75.4) for men. Survival from onset was longer for R-MS (49.7 years; 95% CI 47.9 to 51.5) than for PPMS (32.5 years; 95% CI 29.5 to 35.7); however, survival age was similar. The overall standardised mortality ratios was 2.89 (95% CI 2.71 to 3.07), and patients survived approximately 6 years less than expected, relative to the general population. PPMS had a higher relative mortality risk compared with R-MS (relative mortality ratio (RMR) 1.52; 95% CI 1.30 to 1.80). Women with PPMS had a relative survival disadvantage compared with men with PPMS (RMR 1.55; 95% CI 1.19 to 2.01). Relative survival within 10 years of cohort entry was similar between time periods. CONCLUSIONS: Some of the longest MS survival times are reported here but the risk of death was still greater than in the age, sex and calendar year matched general population. No evidence of increased survival over time was found when improved survival in the general population was taken into consideration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".