A framework for quantifying net benefits of alternative prognostic models

Eleni Rapsomaniki; Ian R. White; Angela M. Wood; Simon G. Thompson; R. W. Tipping; C. E. Ford; L. M. Simpson; A. R. Folsom; L. E. Chambless; D. B. Panagiotakos; C. Pitsavos; C. Chrysohoou; C. Stefanadis; M. Knuiman; P. H. Whincup; S. G. Wannamethee; R. W. Morris; S. Kiechl; J. Willeit; F. Oberhollenzer; A. Mayr; N. Wald; D. A. Lawlor; J. W. Yarnell; J. Gallacher; E. Casiglia; V. Tikhonoff; P. J. Nietert; S. E. Sutherland; D. L. Bachman; J. E. Keil; M. Cushman; R. Tracy; A. Tybjærg-Hansen; B. G. Nordestgaard; R. Frikke-Schmidt; S. Giampaoli; L. Palmieri; S. Panico; D. Vanuzzo; L. Pilotto; A. Gómez de la Cámara; J. A. Gómez Gerique; L. Simons; J. McCallum; Y. Friedlander; A. J. Lee; J. Taylor; J. M. Guralnik; R. Wallace; J. M. Guralnik; D. G. Blazer; J. M. Guralnik; J. M. Guralnik; K. T. Khaw; B. Schöttker; H. Müller; D. Rothenbacher; J. H. Jansson; P. Wennberg; A. Nissinen; C. Donfrancesco; S. Giampaoli; V. Salomaa; K. Harald; P. Jousilahti; E. Vartiainen; M. Woodward; R. B. D'Agostino; P. A. Wolf; R. S. Vasan; M. J. Pencina; E. M. Bladbjerg; T. Jørgensen; L. Møller; J. Jespersen; R. Dankner; A. Chetrit; F. Lubin; A. Rosengren; G. Lappas; H. Eriksson; C. Björkelund; L. Lissner; C. Bengtsson; D. Nagel; Y. Kiyohara; H. Arima; Y. Doi; T. Ninomiya; B. Rodriguez; J. M. Dekker; G. Nijpels; C. D A Stehouwer; H. Iso; A. Kitamura; K. Yamagishi; H. Noda; U. Goldbourt; J. Kauhanen; J. T. Salonen; J. A. Cooper; W. M M Verschuren; A. Blokstra; M. Cushman; A. R. Folsom; S. Shea; A. Döring; C. Meisinger; W. M M Verschuren; A. Blokstra; H. B. Bueno-de-Mesquita; A. Rosengren; G. Lappas; L. H. Kuller; G. Grandits; R. F. Gillum; M. Mussolino; J. A. Cooper; K. A. Bauer; S. Kirkland; J. Shaffer; M. R. Korin; A. Kitamura; H. Iso; S. Sato; P. Amouyel; D. Arveiler; A. Evans; J. Ferrières; H. Schulte; G. Assmann; R. G. Westendorp; B. M. Buckley; C. J. Packard; N. Sattar; B. Cantin; J. P. Després; G. R. Dagenais; E. Barrett-Connor; D. L. Wingard; R. Bettencourt; V. Gudnason; T. Aspelund; G. Sigurdsson; B. Thorsson; J. Witteman; I. Kardys; H. Tiemeier; A. Hofman; H. Tunstall-Pedoe; R. Tavendale; G. D O Lowe; M. Woodward; B. V. Howard; Y. Zhang; L. Best; J. Umans; Y. Ben-Shlomo; G. Davey-Smith; I. Njølstad; T. Wilsgaard; E. Ingelsson; L. Lind; V. Giedraitis; L. Lannfelt; J. M. Gaziano; M. Stampfer; P. Ridker; J. M. Gaziano; P. Ridker; S. Wassertheil-Smoller; J. E. Manson; M. Marmot; R. Clarke; A. Fletcher; E. Brunner; M. Shipley; P. Ridker; J. Buring; J. Shepherd; S. M. Cobbe; I. Ford; M. Robertson; A. Marín Ibañez; E. J M Feskens; D. Kromhout

doi:10.1002/sim.4362

A framework for quantifying net benefits of alternative prognostic models

Eleni Rapsomaniki, Ian R. White, Angela M. Wood, Simon G. Thompson, R. W. Tipping, C. E. Ford, L. M. Simpson, A. R. Folsom, L. E. Chambless, D. B. Panagiotakos, C. Pitsavos, C. Chrysohoou, C. Stefanadis, M. Knuiman, P. H. Whincup, S. G. Wannamethee, R. W. Morris, S. Kiechl, J. Willeit, F. OberhollenzerA. Mayr, N. Wald, D. A. Lawlor, J. W. Yarnell, J. Gallacher, E. Casiglia, V. Tikhonoff, P. J. Nietert, S. E. Sutherland, D. L. Bachman, J. E. Keil, M. Cushman, R. Tracy, A. Tybjærg-Hansen, B. G. Nordestgaard, R. Frikke-Schmidt, S. Giampaoli, L. Palmieri, S. Panico, D. Vanuzzo, L. Pilotto, A. Gómez de la Cámara, J. A. Gómez Gerique, L. Simons, J. McCallum, Y. Friedlander, A. J. Lee, J. Taylor, J. M. Guralnik, R. Wallace, J. M. Guralnik, D. G. Blazer, J. M. Guralnik, J. M. Guralnik, K. T. Khaw, B. Schöttker, H. Müller, D. Rothenbacher, J. H. Jansson, P. Wennberg, A. Nissinen, C. Donfrancesco, S. Giampaoli, V. Salomaa, K. Harald, P. Jousilahti, E. Vartiainen, M. Woodward, R. B. D'Agostino, P. A. Wolf, R. S. Vasan, M. J. Pencina, E. M. Bladbjerg, T. Jørgensen, L. Møller, J. Jespersen, R. Dankner, A. Chetrit, F. Lubin, A. Rosengren, G. Lappas, H. Eriksson, C. Björkelund, L. Lissner, C. Bengtsson, D. Nagel, Y. Kiyohara, H. Arima, Y. Doi, T. Ninomiya, B. Rodriguez, J. M. Dekker, G. Nijpels, C. D A Stehouwer, H. Iso, A. Kitamura, K. Yamagishi, H. Noda, U. Goldbourt, J. Kauhanen, J. T. Salonen, J. A. Cooper, W. M M Verschuren, A. Blokstra, M. Cushman, A. R. Folsom, S. Shea, A. Döring, C. Meisinger, W. M M Verschuren, A. Blokstra, H. B. Bueno-de-Mesquita, A. Rosengren, G. Lappas, L. H. Kuller, G. Grandits, R. F. Gillum, M. Mussolino, J. A. Cooper, K. A. Bauer, S. Kirkland, J. Shaffer, M. R. Korin, A. Kitamura, H. Iso, S. Sato, P. Amouyel, D. Arveiler, A. Evans, J. Ferrières, H. Schulte, G. Assmann, R. G. Westendorp, B. M. Buckley, C. J. Packard, N. Sattar, B. Cantin, J. P. Després, G. R. Dagenais, E. Barrett-Connor, D. L. Wingard, R. Bettencourt, V. Gudnason, T. Aspelund, G. Sigurdsson, B. Thorsson, J. Witteman, I. Kardys, H. Tiemeier, A. Hofman, H. Tunstall-Pedoe, R. Tavendale, G. D O Lowe, M. Woodward, B. V. Howard, Y. Zhang, L. Best, J. Umans, Y. Ben-Shlomo, G. Davey-Smith, I. Njølstad, T. Wilsgaard, E. Ingelsson, L. Lind, V. Giedraitis, L. Lannfelt, J. M. Gaziano, M. Stampfer, P. Ridker, J. M. Gaziano, P. Ridker, S. Wassertheil-Smoller, J. E. Manson, M. Marmot, R. Clarke, A. Fletcher, E. Brunner, M. Shipley, P. Ridker, J. Buring, J. Shepherd, S. M. Cobbe, I. Ford, M. Robertson, A. Marín Ibañez, E. J M Feskens, D. Kromhout

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks.

Original language	English (US)
Pages (from-to)	114-130
Number of pages	17
Journal	Statistics in Medicine
Volume	31
Issue number	2
DOIs	https://doi.org/10.1002/sim.4362
State	Published - Jan 30 2012

Keywords

Cardiovascular disease
Competing risks
Cost-effectiveness
Meta-analysis
Net benefit
Screening strategies

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/sim.4362

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Rapsomaniki, E., White, I. R., Wood, A. M., Thompson, S. G., Tipping, R. W., Ford, C. E., Simpson, L. M., Folsom, A. R., Chambless, L. E., Panagiotakos, D. B., Pitsavos, C., Chrysohoou, C., Stefanadis, C., Knuiman, M., Whincup, P. H., Wannamethee, S. G., Morris, R. W., Kiechl, S., Willeit, J., ... Kromhout, D. (2012). A framework for quantifying net benefits of alternative prognostic models. Statistics in Medicine, 31(2), 114-130. https://doi.org/10.1002/sim.4362

Rapsomaniki, E, White, IR, Wood, AM, Thompson, SG, Tipping, RW, Ford, CE, Simpson, LM, Folsom, AR, Chambless, LE, Panagiotakos, DB, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Whincup, PH, Wannamethee, SG, Morris, RW, Kiechl, S, Willeit, J, Oberhollenzer, F, Mayr, A, Wald, N, Lawlor, DA, Yarnell, JW, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, PJ, Sutherland, SE, Bachman, DL, Keil, JE, Cushman, M, Tracy, R, Tybjærg-Hansen, A, Nordestgaard, BG, Frikke-Schmidt, R, Giampaoli, S, Palmieri, L, Panico, S, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, JA, Simons, L, McCallum, J, Friedlander, Y, Lee, AJ, Taylor, J, Guralnik, JM, Wallace, R, Guralnik, JM, Blazer, DG, Guralnik, JM, Guralnik, JM, Khaw, KT, Schöttker, B, Müller, H, Rothenbacher, D, Jansson, JH, Wennberg, P, Nissinen, A, Donfrancesco, C, Giampaoli, S, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, RB, Wolf, PA, Vasan, RS, Pencina, MJ, Bladbjerg, EM, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Nagel, D, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, JM, Nijpels, G, Stehouwer, CDA, Iso, H, Kitamura, A, Yamagishi, K, Noda, H, Goldbourt, U, Kauhanen, J, Salonen, JT, Cooper, JA, Verschuren, WMM, Blokstra, A, Cushman, M, Folsom, AR, Shea, S, Döring, A, Meisinger, C, Verschuren, WMM, Blokstra, A, Bueno-de-Mesquita, HB, Rosengren, A, Lappas, G, Kuller, LH, Grandits, G, Gillum, RF, Mussolino, M, Cooper, JA, Bauer, KA, Kirkland, S, Shaffer, J, Korin, MR, Kitamura, A, Iso, H, Sato, S, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Westendorp, RG, Buckley, BM, Packard, CJ, Sattar, N, Cantin, B, Després, JP, Dagenais, GR, Barrett-Connor, E, Wingard, DL, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Witteman, J, Kardys, I, Tiemeier, H, Hofman, A, Tunstall-Pedoe, H, Tavendale, R, Lowe, GDO, Woodward, M, Howard, BV, Zhang, Y, Best, L, Umans, J, Ben-Shlomo, Y, Davey-Smith, G, Njølstad, I, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, JM, Stampfer, M, Ridker, P, Gaziano, JM, Ridker, P, Wassertheil-Smoller, S, Manson, JE, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Ridker, P, Buring, J, Shepherd, J, Cobbe, SM, Ford, I, Robertson, M, Marín Ibañez, A, Feskens, EJM & Kromhout, D 2012, 'A framework for quantifying net benefits of alternative prognostic models', Statistics in Medicine, vol. 31, no. 2, pp. 114-130. https://doi.org/10.1002/sim.4362

@article{7168dbb11ab24948b0ce014ceaae97ac,

title = "A framework for quantifying net benefits of alternative prognostic models",

abstract = "New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks.",

keywords = "Cardiovascular disease, Competing risks, Cost-effectiveness, Meta-analysis, Net benefit, Screening strategies",

author = "Eleni Rapsomaniki and White, {Ian R.} and Wood, {Angela M.} and Thompson, {Simon G.} and Tipping, {R. W.} and Ford, {C. E.} and Simpson, {L. M.} and Folsom, {A. R.} and Chambless, {L. E.} and Panagiotakos, {D. B.} and C. Pitsavos and C. Chrysohoou and C. Stefanadis and M. Knuiman and Whincup, {P. H.} and Wannamethee, {S. G.} and Morris, {R. W.} and S. Kiechl and J. Willeit and F. Oberhollenzer and A. Mayr and N. Wald and Lawlor, {D. A.} and Yarnell, {J. W.} and J. Gallacher and E. Casiglia and V. Tikhonoff and Nietert, {P. J.} and Sutherland, {S. E.} and Bachman, {D. L.} and Keil, {J. E.} and M. Cushman and R. Tracy and A. Tybj{\ae}rg-Hansen and Nordestgaard, {B. G.} and R. Frikke-Schmidt and S. Giampaoli and L. Palmieri and S. Panico and D. Vanuzzo and L. Pilotto and {G{\'o}mez de la C{\'a}mara}, A. and {G{\'o}mez Gerique}, {J. A.} and L. Simons and J. McCallum and Y. Friedlander and Lee, {A. J.} and J. Taylor and Guralnik, {J. M.} and R. Wallace and Guralnik, {J. M.} and Blazer, {D. G.} and Guralnik, {J. M.} and Guralnik, {J. M.} and Khaw, {K. T.} and B. Sch{\"o}ttker and H. M{\"u}ller and D. Rothenbacher and Jansson, {J. H.} and P. Wennberg and A. Nissinen and C. Donfrancesco and S. Giampaoli and V. Salomaa and K. Harald and P. Jousilahti and E. Vartiainen and M. Woodward and D'Agostino, {R. B.} and Wolf, {P. A.} and Vasan, {R. S.} and Pencina, {M. J.} and Bladbjerg, {E. M.} and T. J{\o}rgensen and L. M{\o}ller and J. Jespersen and R. Dankner and A. Chetrit and F. Lubin and A. Rosengren and G. Lappas and H. Eriksson and C. Bj{\"o}rkelund and L. Lissner and C. Bengtsson and D. Nagel and Y. Kiyohara and H. Arima and Y. Doi and T. Ninomiya and B. Rodriguez and Dekker, {J. M.} and G. Nijpels and Stehouwer, {C. D A} and H. Iso and A. Kitamura and K. Yamagishi and H. Noda and U. Goldbourt and J. Kauhanen and Salonen, {J. T.} and Cooper, {J. A.} and Verschuren, {W. M M} and A. Blokstra and M. Cushman and Folsom, {A. R.} and S. Shea and A. D{\"o}ring and C. Meisinger and Verschuren, {W. M M} and A. Blokstra and Bueno-de-Mesquita, {H. B.} and A. Rosengren and G. Lappas and Kuller, {L. H.} and G. Grandits and Gillum, {R. F.} and M. Mussolino and Cooper, {J. A.} and Bauer, {K. A.} and S. Kirkland and J. Shaffer and Korin, {M. R.} and A. Kitamura and H. Iso and S. Sato and P. Amouyel and D. Arveiler and A. Evans and J. Ferri{\`e}res and H. Schulte and G. Assmann and Westendorp, {R. G.} and Buckley, {B. M.} and Packard, {C. J.} and N. Sattar and B. Cantin and Despr{\'e}s, {J. P.} and Dagenais, {G. R.} and E. Barrett-Connor and Wingard, {D. L.} and R. Bettencourt and V. Gudnason and T. Aspelund and G. Sigurdsson and B. Thorsson and J. Witteman and I. Kardys and H. Tiemeier and A. Hofman and H. Tunstall-Pedoe and R. Tavendale and Lowe, {G. D O} and M. Woodward and Howard, {B. V.} and Y. Zhang and L. Best and J. Umans and Y. Ben-Shlomo and G. Davey-Smith and I. Nj{\o}lstad and T. Wilsgaard and E. Ingelsson and L. Lind and V. Giedraitis and L. Lannfelt and Gaziano, {J. M.} and M. Stampfer and P. Ridker and Gaziano, {J. M.} and P. Ridker and S. Wassertheil-Smoller and Manson, {J. E.} and M. Marmot and R. Clarke and A. Fletcher and E. Brunner and M. Shipley and P. Ridker and J. Buring and J. Shepherd and Cobbe, {S. M.} and I. Ford and M. Robertson and {Mar{\'i}n Iba{\~n}ez}, A. and Feskens, {E. J M} and D. Kromhout",

year = "2012",

month = jan,

day = "30",

doi = "10.1002/sim.4362",

language = "English (US)",

volume = "31",

pages = "114--130",

journal = "Statistics in Medicine",

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T1 - A framework for quantifying net benefits of alternative prognostic models

AU - Rapsomaniki, Eleni

AU - White, Ian R.

AU - Wood, Angela M.

AU - Thompson, Simon G.

AU - Tipping, R. W.

AU - Ford, C. E.

AU - Simpson, L. M.

AU - Folsom, A. R.

AU - Chambless, L. E.

AU - Panagiotakos, D. B.

AU - Pitsavos, C.

AU - Chrysohoou, C.

AU - Stefanadis, C.

AU - Knuiman, M.

AU - Whincup, P. H.

AU - Wannamethee, S. G.

AU - Morris, R. W.

AU - Kiechl, S.

AU - Willeit, J.

AU - Oberhollenzer, F.

AU - Mayr, A.

AU - Wald, N.

AU - Lawlor, D. A.

AU - Yarnell, J. W.

AU - Gallacher, J.

AU - Casiglia, E.

AU - Tikhonoff, V.

AU - Nietert, P. J.

AU - Sutherland, S. E.

AU - Bachman, D. L.

AU - Keil, J. E.

AU - Cushman, M.

AU - Tracy, R.

AU - Tybjærg-Hansen, A.

AU - Nordestgaard, B. G.

AU - Frikke-Schmidt, R.

AU - Giampaoli, S.

AU - Palmieri, L.

AU - Panico, S.

AU - Vanuzzo, D.

AU - Pilotto, L.

AU - Gómez de la Cámara, A.

AU - Gómez Gerique, J. A.

AU - Simons, L.

AU - McCallum, J.

AU - Friedlander, Y.

AU - Lee, A. J.

AU - Taylor, J.

AU - Guralnik, J. M.

AU - Wallace, R.

AU - Guralnik, J. M.

AU - Blazer, D. G.

AU - Guralnik, J. M.

AU - Khaw, K. T.

AU - Schöttker, B.

AU - Müller, H.

AU - Rothenbacher, D.

AU - Jansson, J. H.

AU - Wennberg, P.

AU - Nissinen, A.

AU - Donfrancesco, C.

AU - Giampaoli, S.

AU - Salomaa, V.

AU - Harald, K.

AU - Jousilahti, P.

AU - Vartiainen, E.

AU - Woodward, M.

AU - D'Agostino, R. B.

AU - Wolf, P. A.

AU - Vasan, R. S.

AU - Pencina, M. J.

AU - Bladbjerg, E. M.

AU - Jørgensen, T.

AU - Møller, L.

AU - Jespersen, J.

AU - Dankner, R.

AU - Chetrit, A.

AU - Lubin, F.

AU - Rosengren, A.

AU - Lappas, G.

AU - Eriksson, H.

AU - Björkelund, C.

AU - Lissner, L.

AU - Bengtsson, C.

AU - Nagel, D.

AU - Kiyohara, Y.

AU - Arima, H.

AU - Doi, Y.

AU - Ninomiya, T.

AU - Rodriguez, B.

AU - Dekker, J. M.

AU - Nijpels, G.

AU - Stehouwer, C. D A

AU - Iso, H.

AU - Kitamura, A.

AU - Yamagishi, K.

AU - Noda, H.

AU - Goldbourt, U.

AU - Kauhanen, J.

AU - Salonen, J. T.

AU - Cooper, J. A.

AU - Verschuren, W. M M

AU - Blokstra, A.

AU - Cushman, M.

AU - Folsom, A. R.

AU - Shea, S.

AU - Döring, A.

AU - Meisinger, C.

AU - Verschuren, W. M M

AU - Blokstra, A.

AU - Bueno-de-Mesquita, H. B.

AU - Rosengren, A.

AU - Lappas, G.

AU - Kuller, L. H.

AU - Grandits, G.

AU - Gillum, R. F.

AU - Mussolino, M.

AU - Cooper, J. A.

AU - Bauer, K. A.

AU - Kirkland, S.

AU - Shaffer, J.

AU - Korin, M. R.

AU - Kitamura, A.

AU - Iso, H.

AU - Sato, S.

AU - Amouyel, P.

AU - Arveiler, D.

AU - Evans, A.

AU - Ferrières, J.

AU - Schulte, H.

AU - Assmann, G.

AU - Westendorp, R. G.

AU - Buckley, B. M.

AU - Packard, C. J.

AU - Sattar, N.

AU - Cantin, B.

AU - Després, J. P.

AU - Dagenais, G. R.

AU - Barrett-Connor, E.

AU - Wingard, D. L.

AU - Bettencourt, R.

AU - Gudnason, V.

AU - Aspelund, T.

AU - Sigurdsson, G.

AU - Thorsson, B.

AU - Witteman, J.

AU - Kardys, I.

AU - Tiemeier, H.

AU - Hofman, A.

AU - Tunstall-Pedoe, H.

AU - Tavendale, R.

AU - Lowe, G. D O

AU - Woodward, M.

AU - Howard, B. V.

AU - Zhang, Y.

AU - Best, L.

AU - Umans, J.

AU - Ben-Shlomo, Y.

AU - Davey-Smith, G.

AU - Njølstad, I.

AU - Wilsgaard, T.

AU - Ingelsson, E.

AU - Lind, L.

AU - Giedraitis, V.

AU - Lannfelt, L.

AU - Gaziano, J. M.

AU - Stampfer, M.

AU - Ridker, P.

AU - Gaziano, J. M.

AU - Ridker, P.

AU - Wassertheil-Smoller, S.

AU - Manson, J. E.

AU - Marmot, M.

AU - Clarke, R.

AU - Fletcher, A.

AU - Brunner, E.

AU - Shipley, M.

AU - Ridker, P.

AU - Buring, J.

AU - Shepherd, J.

AU - Cobbe, S. M.

AU - Ford, I.

AU - Robertson, M.

AU - Marín Ibañez, A.

AU - Feskens, E. J M

AU - Kromhout, D.

PY - 2012/1/30

Y1 - 2012/1/30

N2 - New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks.

AB - New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks.

KW - Cardiovascular disease

KW - Competing risks

KW - Cost-effectiveness

KW - Meta-analysis

KW - Net benefit

KW - Screening strategies

UR - http://www.scopus.com/inward/record.url?scp=84855240264&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84855240264&partnerID=8YFLogxK

U2 - 10.1002/sim.4362

DO - 10.1002/sim.4362

M3 - Article

C2 - 21905066

AN - SCOPUS:84855240264

VL - 31

SP - 114

EP - 130

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 2

ER -

A framework for quantifying net benefits of alternative prognostic models

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UN SDGs

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