Time and expected value of sample information wait for no patient

被引:35
作者
Eckermann, Simon [1 ]
Willan, Andrew R. [2 ,3 ]
机构
[1] Flinders Univ S Australia, Flinders Ctr Clin Change & Hlth Care Res, Adelaide, SA 5001, Australia
[2] Univ Toronto, Toronto, ON, Canada
[3] SickKids Res Inst, Toronto, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
expected value of sample information; methods; optimal trial design; time;
D O I
10.1111/j.1524-4733.2007.00296.x
中图分类号
F [经济];
学科分类号
02 [经济学];
摘要
Objective: The expected value of sample information (EVSI) from prospective trials has previously been modeled as the product of EVSI per patient, and the number of patients across the relevant time horizon less those "used up" in trials. However, this implicitly assumes the eligible patient population to which information from a trial can be applied across a time horizon are independent of time for trial accrual, follow-up and analysis. Methods: This article demonstrates that in calculating the EVSI of a trial, the number of patients who benefit from trial information should be reduced by those treated outside as well as within the trial over the time until trial evidence is updated, including time for accrual, follow-up and analysis. Results: Accounting for time is shown to reduce the eligible patient population: 1) independent of the size of trial in allowing for time of follow-up and analysis, and 2) dependent on the size of trial for time of accrual, where the patient accrual rate is less than incidence. Consequently, the EVSI and expected net gain (ENG) at any given trial size are shown to be lower when accounting for time, with lower ENG reinforced in the case of trials undertaken while delaying decisions by additional opportunity costs of time. Conclusions: Appropriately accounting for time reduces the EVSI of trial design and increase opportunity costs of trials undertaken with delay, leading to lower likelihood of trialing being optimal and smaller trial designs where optimal.
引用
收藏
页码:522 / 526
页数:5
相关论文
共 10 条
[1]
Expected value of sample information calculations in medical decision modeling [J].
Ades, AE ;
Lu, G ;
Claxton, K .
MEDICAL DECISION MAKING, 2004, 24 (02) :207-227
[2]
A rational framework for decision making by the National Institute for Clinical Excellence (NICE) [J].
Claxton, K ;
Sculpher, M ;
Drummond, M .
LANCET, 2002, 360 (9334) :711-715
[3]
The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies [J].
Claxton, K .
JOURNAL OF HEALTH ECONOMICS, 1999, 18 (03) :341-364
[4]
A dynamic programming approach to the efficient design of clinical trials [J].
Claxton, K ;
Thompson, KM .
JOURNAL OF HEALTH ECONOMICS, 2001, 20 (05) :797-822
[5]
ECKERMANN S, 2007, CTR APPL EC RES, V6
[6]
Expected value of information and decision making in HTA [J].
Eckermann, Simon ;
Willan, Andrew R. .
HEALTH ECONOMICS, 2007, 16 (02) :195-209
[7]
External cephalic version beginning at 34 weeks' gestation versus 37 weeks' gestation: A randomized multicenter trial [J].
Hutton, EK ;
Kaufman, K ;
Hodnett, E ;
Amankwah, K ;
Hewson, SA ;
McKay, D ;
Szalai, JP ;
Hannah, ME .
AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2003, 189 (01) :245-254
[8]
RAIFFA H, 1967, APPL STAT DECISION T
[9]
Schlaiffer R., 1958, PROBABILITY STAT BUS, pMcGraw
[10]
The value of information and optimal clinical trials design (vol 24, pg 1971, 2005) [J].
Willan, AR .
STATISTICS IN MEDICINE, 2006, 25 (04) :720-720