Aneurysm occlusion in elderly patients with aneurysmal subarachnoid haemorrhage: a cost-utility analysis.
BACKGROUND
Aneurysm occlusion after subarachnoid haemorrhage (SAH) aims to improve outcome by reducing the rebleeding risk. With increasing age, overall prognosis decreases, and the complications of aneurysm occlusion increase. The balance of risks for aneurysm occlusion in elderly SAH patients in different age categories and clinical conditions is unknown.


METHODS
A Markov model was used to evaluate quality-adjusted life years (QALY), additional costs and incremental cost-effectiveness ratios (ICER) of aneurysm occlusion in 192 patient subgroups, based on age, gender, neurological condition at admission, time since SAH, and aneurysm size and location. Probabilistic sensitivity analyses were performed.


RESULTS
For patients admitted in poor condition ≥ 10 days after SAH, and patients older than 80 years, admitted in poor condition admitted ≥ 4 days after SAH, occlusion implied QALY loss and increased costs. Only for women younger than 79 and men younger than 74 years admitted in good condition within 4 days did the ICER of occlusion fall below €50,000 per QALY. Occlusion was beneficial and cost-saving in women aged 74 years or younger admitted in good condition within 4 days with a small posterior circulation aneurysm. Conclusions Aneurysm occlusion is harmful in some subgroups of elderly patients and beneficial in others. It is cost-effective only in specific subgroups that comprise a large part of the patients encountered in clinical practice. Beyond the age of 80 years, the balance between risks and benefits is often no longer positive for occlusion, and it should only be considered if the predicted life expectancy leaves margin for benefit.
Koffijberg
H
H
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, STR 6.131, PO Box 85500, Utrecht 3508 GA, The Netherlands. h.koffijberg@umcutrecht.nl
Buskens
E
E
Rinkel
G J E
GJ
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method; D019635:Neurosurgical Procedures / Q000191:economics*; D011336:Probability; D011379:Prognosis; D019057:Quality-Adjusted Life Years; D018570:Risk Assessment; D012737:Sex Factors; D013345:Subarachnoid Hemorrhage / Q000191:economics* / Q000473:pathology / Q000601:surgery*; D016896:Treatment Outcome