Modelling of endpoint postponement for all-cause mortality in statin trials

M. R. Hansen, Anton Pottegård, A. Hrobjartsson, P. Damkier, R. D. Christensen, Kasper Søltoft Larsen, M. E. L. Kristensen, P. M. Christensen, J. Hallas

Publikation: Bidrag til tidsskriftKonferenceabstrakt i tidsskriftForskningpeer review

Resumé

Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcome measures, including the "number needed to treat" (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan-Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan-Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial's running time. The underlying assumption was that the mortality was reasonably stable within the trials' running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPs were generally small for estimates based on pixel-counting, -10 and 27days for trials both primary and secondary intervention that typically ran over 1.9- 6.1 years. The modelled EPs varied between -2 and 34 days. The difference between modeled EP and EP based on pixel-counting was between -8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment.
OriginalsprogEngelsk
Artikelnummer1
TidsskriftPharmacoepidemiology and Drug Safety
Vol/bind24
Udgave nummerS1
Sider (fra-til)1
Antal sider1
ISSN1053-8569
DOI
StatusUdgivet - 2015
Begivenhed31st International Conference on Pharmacoepidemiology and Therapeutic Risk Management - Boston, USA
Varighed: 22. aug. 201526. aug. 2015

Konference

Konference31st International Conference on Pharmacoepidemiology and Therapeutic Risk Management
LandUSA
ByBoston
Periode22/08/201526/08/2015

Emneord

  • *mortality *pharmacoepidemiology *risk management *model meta analysis Kaplan Meier method human prophylaxis survival risk survival rate hazard ratio risk factor patient preference *statin (protein) placebo

Citer dette

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title = "Modelling of endpoint postponement for all-cause mortality in statin trials",
abstract = "Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcome measures, including the {"}number needed to treat{"} (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan-Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan-Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial's running time. The underlying assumption was that the mortality was reasonably stable within the trials' running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPs were generally small for estimates based on pixel-counting, -10 and 27days for trials both primary and secondary intervention that typically ran over 1.9- 6.1 years. The modelled EPs varied between -2 and 34 days. The difference between modeled EP and EP based on pixel-counting was between -8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment.",
keywords = "*mortality *pharmacoepidemiology *risk management *model meta analysis Kaplan Meier method human prophylaxis survival risk survival rate hazard ratio risk factor patient preference *statin (protein) placebo",
author = "Hansen, {M. R.} and Anton Potteg{\aa}rd and A. Hrobjartsson and P. Damkier and Christensen, {R. D.} and Larsen, {Kasper S{\o}ltoft} and Kristensen, {M. E. L.} and Christensen, {P. M.} and J. Hallas",
year = "2015",
doi = "10.1002/pds.3838",
language = "English",
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journal = "Pharmacoepidemiology and Drug Safety",
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Modelling of endpoint postponement for all-cause mortality in statin trials. / Hansen, M. R.; Pottegård, Anton; Hrobjartsson, A.; Damkier, P.; Christensen, R. D.; Larsen, Kasper Søltoft; Kristensen, M. E. L.; Christensen, P. M.; Hallas, J.

I: Pharmacoepidemiology and Drug Safety, Bind 24, Nr. S1, 1, 2015, s. 1.

Publikation: Bidrag til tidsskriftKonferenceabstrakt i tidsskriftForskningpeer review

TY - ABST

T1 - Modelling of endpoint postponement for all-cause mortality in statin trials

AU - Hansen, M. R.

AU - Pottegård, Anton

AU - Hrobjartsson, A.

AU - Damkier, P.

AU - Christensen, R. D.

AU - Larsen, Kasper Søltoft

AU - Kristensen, M. E. L.

AU - Christensen, P. M.

AU - Hallas, J.

PY - 2015

Y1 - 2015

N2 - Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcome measures, including the "number needed to treat" (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan-Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan-Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial's running time. The underlying assumption was that the mortality was reasonably stable within the trials' running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPs were generally small for estimates based on pixel-counting, -10 and 27days for trials both primary and secondary intervention that typically ran over 1.9- 6.1 years. The modelled EPs varied between -2 and 34 days. The difference between modeled EP and EP based on pixel-counting was between -8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment.

AB - Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcome measures, including the "number needed to treat" (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan-Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan-Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial's running time. The underlying assumption was that the mortality was reasonably stable within the trials' running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPs were generally small for estimates based on pixel-counting, -10 and 27days for trials both primary and secondary intervention that typically ran over 1.9- 6.1 years. The modelled EPs varied between -2 and 34 days. The difference between modeled EP and EP based on pixel-counting was between -8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment.

KW - mortality pharmacoepidemiology risk management model meta analysis Kaplan Meier method human prophylaxis survival risk survival rate hazard ratio risk factor patient preference statin (protein) placebo

U2 - 10.1002/pds.3838

DO - 10.1002/pds.3838

M3 - Conference abstract in journal

VL - 24

SP - 1

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

SN - 1053-8569

IS - S1

M1 - 1

ER -