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Sequential designs. Métodos Secuenciales. Multiplicidad Múltiples análisis (intermedios, secuenciales) Otras causas: Múltiples criterios de evaluación Múltiples tiempos de observación (medidas repetidas) Múltiples comparaciones: diseños con más de dos tratamientos subgrupos. - PowerPoint PPT Presentation

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  • Sequential designs

  • Mtodos Secuenciales

    Multiplicidad

    Mltiples anlisis (intermedios, secuenciales)

    Otras causas:Mltiples criterios de evaluacinMltiples tiempos de observacin (medidas repetidas)Mltiples comparaciones:diseos con ms de dos tratamientos subgrupos

  • Diseo frecuencista clsico3 pasos bsicos:Estimacin del tamao muestralReclutamiento de la meustraAnlisis estadstico

  • Mtodos secuenciales: justificacinLa informacin en los ensayos clnicos se acumula progresivamente en el tiempoActitudes ante este hecho:Ignorarlo: diseo clsicoMonitorizacin de acontecimientos adversosAprovechar la informacin a medida que se obtiene: diseo secuencial

  • Mtodos secuenciales: justificacin (2)Aparicin de conflictos ticos, sobretodo en enfermedades con pronstico grave

    La hiptesis de trabajo no se ajusta a la realidad:Los tratamientos pueden ser mejores o peores que lo esperado

    Estudios largos aconsejan algn tipo de control de los resultados.

  • Esquema de un estudio estndarAnlisisInicio reclutamientoSeguimiento

  • Esquema de un estudio secuencialAnlisisInicio reclutamientoSeguimiento

  • Clave:Dado que los datos se van acumulando paulatinamente, se podran analizar a ciertos intervalos y tomar decisiones en base a los resultados

    Pero

    Mltiples anlisis pueden llevar a errores estadsticos y decisiones clnicas erroneas

  • Monitorizacin ingenuaK hiptesis independientes: H01 , H02 , ... , H0KS resultados significativos ( p=1)Pr(S=K)Pr(S=K)

    10.05000.05000.800

    20.09750.00250.640

    30.14260.00010.512

    40.18550.00000.410

    50.22620.00000.328

    KPr(S>=1|Ho.)KPr(S>=1|Ho.)

    10.0500100.4013

    20.0975150.5367

    30.1426200.6415

    40.1855250.7226

    50.2262300.7854

    Hoja2

    Hoja3

  • Terminacin prematura de ensayos clnicosPosibles causas:

    Datos acumulados procedentes del ensayoDesarrollo global del estudioInformacin externa al estudio

  • Terminacin prematura de ensayos clnicos1) Datos acumulados procedentes del ensayoEl tratamiento experimental es claramente peorPoca probabilidad de demostrar que el tratamiento experimental es mejorEl tratamiento experimental es mejorEfectos secundarios inesperados / inaceptables

  • Terminacin prematura de ensayos clnicos2) Desarrollo global del estudioImposibilidad de reclutar al ritmo necesarioExcesiva falta de cumplimiento Insuficiente financiacin

  • Terminacin prematura de ensayos clnicos3) Informacin externa al estudioDatos procedentes de otros estudios: beneficio o perjuicioDatos de la prctica clnica habitual: acontecimientos adversos no sospechados e inaceptablesInnovaciones teraputicas que impliquen cambios en los estndares de comparacinRetirada del tratamiento del mercado

  • Ventajas de los mtodos secuencialesticas: La asignacin aleatoria es tica siempre que existan dudas sobre qu tratamiento es mejor

    Econmicas: Requieren menos recursos de tiempo, dinero y esfuerzo

    De poder estadstico: Se mantiene el poder predefinido, independientemente de la variabilidad

    Incentivas: Motivacin al conocer resultados

  • Condiciones de aplicabilidadEl estudio requiere una muestra grandeEl objetivo del estudio es nico y bien definidoSe prev una prolongada duracin del estudioEl resultado para cada paciente se conoce rpidamente, durante la fase de inclusin

  • Diseo NO aplicable a mtodo secuencialAnlisis?Desarrollo totalReclutamiento

  • Diseo S aplicable a mtodo secuencialAnlisisDesarrollo totalReclutamiento

  • Tipos de diseo secuencialReestimacin del tamao muestral2) Mtodos secuenciales por grupos3) Aproximacin por funciones de gasto de a4) Intervalos de confianza repetidos5) Restriccin estocstica6) Mtodos bayesianos7) Lmites continuos (funcin de verosimilitud)

  • Mtodos secuenciales por gruposPocock (1977)Pruebas de significacin repetidasK = N mximo de inspecciones a realizarK fijo a prioriAnlisis con pruebas estadsticas clsicas (2, t-test, ...)

  • Correccin del nivel de significacinUso de un ms estricto que en cada inspeccin: nivel de significacin nominalDiseoPredeterminacin del tamao muestral con para la ltima inspeccin tericaNtotal > NclsicaNgrupo = Ntotal / K

  • Resumen de las caractersticasDiseo y anlisis sencillosAplicable a cualquier tipo de prueba estadstica

    Debe anticiparse el nmero mximo de inspecciones (K)No permite finalizar prematuramente si H0 es cierta

  • Group Sequential Methods

    Hoja1

    O'Brien & FlemingPetoPocock

    Kza'za'za'

    12.7820.0052.5760.0102.1780.029

    21.9670.0491.9690.0492.1780.029

    13.4380.0012.5760.0102.2890.022

    22.4310.0152.5760.0102.2890.022

    31.9850.0471.9690.0492.2890.022

    14.0840.0003.2910.0012.3610.018

    22.8880.0043.2910.0012.3610.018

    32.3580.0183.2910.0012.3610.018

    42.0420.0411.9690.0492.3610.018

    14.5550.0003.2910.0012.4130.016

    23.2210.0013.2910.0012.4130.016

    32.6300.0093.2910.0012.4130.016

    42.2770.0233.2910.0012.4130.016

    52.0370.0421.9690.0492.4130.016

    Hoja2

    Hoja3

  • Implications of Stopping Rules Haybittle-Petodifficult to stop trial earlyalmost no impact on significance level final analysisPocock nominal significance levelseasier to stop trial earlyheavy impact on significance level final analysisOBrien-Flemingvery stringent criterion at first interim analysisrelatively low impact on significance level final analysis

  • Example 1Comparison of drug combinations CP and CVP in non-Hodgkins lymphoma.Measure: tumour shrinkageTrial: over 2 years, about 120 patients.Five interim analyses planned, roughly after every 25th result.Table gives numbers of successes and nominal p-values using a 2 test at each stage.

  • Example 1

    response rates

    Analysis

    CP

    CVP

    statistic & p-value

    1

    3/14

    5/11

    1.63 (p>0.20)

    2

    11/27

    13/24

    0.92 (p>0.30)

    3

    18/40

    17/36

    0.04 (p>0.80)

    4

    18/54

    24/48

    3.25 (0.05

  • Example 1Conclusion: Not significant at end of trial (overall p>0.05) since p>0.016 the required nominal value for 5 repeat testsIf NO interim analyses had been done then conclusion would have been differentCVP declared significantly better at 5% level

  • Example 2Cautionary Example:ref: Br J Surg, (1974), 61: 177 No significant difference with 49 patients The trial was therefore continued After 100 patients gave result 2 = 4.675, d.f. = 1, p< 0.05 (and the trial was published)Actual pvalue is 0.031 > 0.029 so cannot claim 5% significance

  • Funciones de gasto de (1)Lan y DeMets (1983)Mtodos secuenciales por grupos: Especificacin a priori de K Tamao de los grupos fijoRelajan estos requisitos global Funcin de gasto de

  • Alpha spending function approach (2)Pocock: : early stopping for H0 rejectionK = 5= 0,5= 0,05Increase in information (%)U (Normal Distribution)

  • Alpha spending function approach (3)OBrien y Fleming: early stopping for H0 rejectionK=5=0=0,05U (Normal Distribution)Increase in information (%)

  • Conditional powerNegative results:CAST (I-II) study. NEJM (1989 & 1992)Group sequential testing using permutation distribution & stochastic curtailment methodsHPMPC trial, Ann Intern Med 1997ACTG Study 243. NEJM 1998

  • Conditional powerPositive results:CRYO-ROP Arch Ophthalmology,1988 Grable el al. Am J Obstet Gynecol, 1996

    Extension of trial: Proschan MA, Biometrics, 1995

  • Mtodos basados en lmites continuosJ. Whitehead; PESTDefinicin de:Estadsticos Z y VGrfico de representacin de Z y VRegin de continuacinRegla secuencial

  • RepresentacinEjes:abcisas: V informacin acumuladaordenadas: Z diferencias acumuladasRegin de continuacinsegn un modelo secuencialgarantiza las propiedades estadsticas (a y b) si se sigue la regla secuencial

  • Regin de continuacin

  • Mtodos basados en lmites continuosFlexibilidadNmero de inspecciones no limitadoTamao de N grupoFormas de regin variadas

  • Anlisis secuencial segn Z y VSe calcula Z y V a medida que se acumulan los datosRegla secuencialSe finaliza el estudio si la coordenada (Z,V) queda fuera de la regin de continuacinLa conclusin depende del lmite cruzado

  • Ventajas de los mtodos basados en lmites continuosFlexibilidad:Nmero de inspecciones no limitadoTamao de grupo entre inspecciones variableFormas de regin variadas, con diferentes propiedades

  • Frmulas de Z y VEspecficas en funcin de:el tipo de datos:binariosnormalessupervivenciaordinalesla definicin de la diferenciaabsolutarelativa

  • Monitorizacin secuencialPlan de monitorizacin:nmero de respuestas o eventostiempo (calendario)Flexible (ej. ajustes a tasa reclutamiento)DVi independiente de Zi

  • Monitorizacin secuencialFinalizacin del estudio:sobrepasar los lmites de la regin de continuacin

    criterios no relacionados con el resultado de la monitorizacin secuencial

  • Modelo triangular unilateralModelo secuencial de lmites continuos con regin triangular para hiptesis unilateral

  • Modelo triangular bilateral

  • Modelo RPST

  • Modelo Restricted Procedure

  • Modelo RPST truncado

  • Open top design

  • Monitorizacin estudio TIMEuropean Heart Journal, 2000; 21:457-465.

  • TIM study. European Heart Journal. 2000: 21, 457-65

  • Anlisis estudio TIME-PIAMAVCMuerte

    Grfico4

    0.88209986830.63428354031.2267387189

    0.94878455490.71088766841.2662930751

    1.57731053630.87345826832.8483427523

    1.6872861120.95200444422.9904633755

    0.36385909260.14573150560.908475067

    0.38886693440.15757129340.9596766606

    0.81552605350.56428401561.1786311957

    0.87536805780.62676600141.2225762643

    OR

    LI

    LS

    OR

    Mon Pre-Audi

    ABTotalA-BIncrementos

    FechanN%nN%nN%%nNDasdif V

    10-Feb-93000

    Sevilla1-Dec-945846612.45%434569.43%10192210.95%3.02%10192265922.4840

    Lepe1-Jun-956561410.59%576179.24%12212319.91%1.35%213091824.99325

    La Toja27-Nov-957772910.56%677189.33%14414479.95%1.23%222161794.94016

    Barajas20-May-969287210.55%838569.70%175172810.13%0.85%312811756.90188

    Bellaterra4-Feb-97107104410.25%10110359.76%208207910.00%0.49%333512607.47820

    RPST4000RPST4500RPST5000RPST5305RPST6000RPST7000RPST10000RPSTTRIANGULAR

    CorteZVCONTLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINAL

    00.0000.0000.00012.485CONTINUA9.361CONTINUA8.756CONTINUA8.564CONTINUA8.320CONTINUA8.164CONTINUA8.041CONTINUA8.014CONTINUA13.526CONTINUA

    1-6.95222.4842.7644.762CONTINUA1.611CONTINUA0.980CONTINUA0.774CONTINUA0.502CONTINUA0.316CONTINUA0.152CONTINUA0.110CONTINUA3.292CONTINUA

    2-4.14927.4771.3035.123CONTINUA1.966CONTINUA1.329CONTINUA1.119CONTINUA0.841CONTINUA0.649CONTINUA0.476CONTINUA0.430CONTINUA3.095CONTINUA

    3-4.45332.4171.2964.041CONTINUA0.877CONTINUA0.234CONTINUA0.022CONTINUA-0.262CONTINUA-0.461CONTINUA-0.643CONTINUA-0.692CONTINUA1.461CONTINUA

    4-3.69039.3191.5322.283CONTINUA-0.889CONTINUA-1.540CONTINUA-1.757CONTINUA-2.049CONTINUA-2.257CONTINUA-2.452CONTINUA-2.506CONTINUA-1.068CONTINUA

    5-2.55046.7971.5940.571CONTINUA-2.610STOP-3.269STOP-3.491STOP-3.793STOP-4.010STOP-4.219STOP-4.278STOP-3.615STOP

    p valores

    E-P

    Anlisis ajustado

    Test no sesgadoTest de Wald

    Distribucin Chi2Distribucin normalDistribucin normal

    ChipUpUp

    0.3030120.5820000.5504660.5820000.7455280.455952

    Anlisis crudo

    Distribucin Chi2Distribucin normal

    ChipUp

    0.1274300.7211120.3569730.721112

    Variables secundarias

    Anlisis ajustado (test Wald)Anlisis crudo

    Distribucin normalDistribucin Chi2Distribucin normal

    UpChipUp

    IAM1.51131840.13070743.2097600.0732001.7915800.073200

    AVC2.16561310.03034074.1999770.0404252.0493850.040424

    Muerte1.08529280.27779210.6099200.4348180.7809740.434818

    Ana Pre-Audi

    ANALISIS

    p =0.549

    EstimadorEstimacinSE (Est)lils% Equiv%ICZL Eq InfL Eq SupEq InfEq SupEquiv

    Theta mle-0.0540.146-0.2950.18620%901.6448530.0440.065NoNoNo

    Theta mediana-0.094-0.3830.16020%901.6448530.0750.112NoNoNo

    Theta ajustada-0.1290.166-0.4020.14420%901.6448530.1030.155NoSNo

    OR (tetha mle)0.9470.7451.20420%901.6448530.7581.136NoNoNo

    OR (tetha mediana)0.9110.6821.17420%901.6448530.7291.093NoNoNo

    OR (tetha ajustada)0.8791.1800.6691.15520%901.6448530.7031.055NoNoNo

    p(exp) (mediana)9.585%20%901.644853

    p(con) (mediana)10.428%20%901.644853

    Diferencia proporciones0.842%20%901.6448530.674%1.011%

    EstimadorEstimacinSE (Est)lils% Equiv%ICZL Eq InfL Eq SupEq InfEq SupEquiv

    Theta mle-0.0540.146-0.3410.23220%951.9599610.0440.065NoNoNo

    Theta mediana-0.094-0.4600.20820%951.9599610.0750.112NoNoNo

    Theta ajustada-0.1290.166-0.4540.19620%951.9599610.1030.155NoNoNo

    OR (tetha mle)0.9470.7111.26120%951.9599610.7581.136NoNoNo

    OR (tetha mediana)0.9110.6311.23120%951.9599610.7291.093NoNoNo

    OR (tetha ajustada)0.8791.1800.6351.21720%951.9599610.7031.055NoNoNo

    p(exp) (mediana)9.585%20%951.959961

    p(con) (mediana)10.428%20%951.959961

    Diferencia proporciones0.842%20%951.9599610.674%1.011%

    Mon Post-Audi

    ABTotalA-BIncrementos

    FechanN%nN%nN%%nNDasdif V

    Sevilla1-Dec-945344811.830%394418.844%9288910.349%2.987%92889020.6198

    Lepe1-Jun-956358810.714%535898.998%11611779.856%1.716%242881825.52209

    La Toja27-Nov-956968410.088%616818.957%13013659.524%1.130%141881793.26288

    Barajas20-May-968581810.391%738009.125%15816189.765%1.266%282531756.23801

    Bellaterra4-Feb-9710510689.831%9910569.375%20421249.605%0.456%4650626010.45893

    RPST4000RPST4500RPST5000RPST5305RPST6000RPST7000RPST10000RPSTTRIANGULAR

    CorteZVCONTLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINALLIMITEFINAL

    00.0000.0000.00012.485CONTINUA9.361CONTINUA8.756CONTINUA8.564CONTINUA8.320CONTINUA8.164CONTINUA8.041CONTINUA8.014CONTINUA13.526CONTINUA

    1-6.63820.6202.6475.290CONTINUA2.142CONTINUA1.512CONTINUA1.308CONTINUA1.038CONTINUA0.855CONTINUA0.694CONTINUA0.653CONTINUA4.029CONTINUA

    2-5.04926.1421.3705.350CONTINUA2.195CONTINUA1.559CONTINUA1.351CONTINUA1.074CONTINUA0.884CONTINUA0.713CONTINUA0.668CONTINUA3.472CONTINUA

    3-3.85729.4051.0534.948CONTINUA1.788CONTINUA1.149CONTINUA0.938CONTINUA0.658CONTINUA0.463CONTINUA0.286CONTINUA0.239CONTINUA2.705CONTINUA

    4-5.12135.6431.4563.169CONTINUA0.002CONTINUA-0.645CONTINUA-0.859CONTINUA-1.147CONTINUA-1.350CONTINUA-1.539CONTINUA-1.590CONTINUA0.229CONTINUA

    5-2.42446.1021.8850.434CONTINUA-2.747STOP-3.406STOP-3.627STOP-3.927STOP-4.144STOP-4.352STOP-4.410STOP-3.675STOP

    Ana Post-Audi

    ANALISIS

    p =0.582

    EstimadorEstimacinSE (Est)lils% Equiv%ICZL Eq InfL Eq SupEq InfEq SupEquiv

    Theta mle-0.05260.147-0.2950.19020%901.640.0420.063NoNoNo

    Theta mediana-0.086-0.3760.16820%901.640.0690.104NoNoNo

    Theta ajustada-0.1250.168-0.4020.15120%901.640.1000.151NoNoNo

    OR (tetha mle)0.9490.7451.20920%901.640.7591.139NoNoNo

    OR (tetha mediana)0.9170.6871.18320%901.640.7341.101NoNoNo

    OR (tetha ajustada)0.8821.1830.6691.16320%901.640.7061.059NoNoNo

    p(exp) (mediana)9.248%20%901.64

    p(con) (mediana)10.060%20%901.64

    Diferencia proporciones0.812%20%901.640.649%0.974%

    EstimadorEstimacinSE (Est)lils% Equiv%ICZL Eq InfL Eq SupEq InfEq SupEquiv

    Theta mle-0.0530.147-0.3410.23620%951.960.0420.063NoNoNo

    Theta mediana-0.086-0.4560.21620%951.960.0690.104NoNoNo

    Theta ajustada-0.1250.168-0.4550.20420%951.960.1000.151NoNoNo

    OR (tetha mle)0.9490.7111.26620%951.960.7591.139NoNoNo

    OR (tetha mediana)0.9170.6341.24120%951.960.7341.101NoNoNo

    OR (tetha ajustada)0.8821.1830.6341.22720%951.960.7061.059NoNoNo

    p(exp) (mediana)9.248%20%951.96No

    p(con) (mediana)10.060%20%951.96No

    Diferencia proporciones0.812%20%951.960.649%0.974%

    Anlisis secundarios

    ABTotalA-B

    nN%nN%nN%%

    E-P10510689.83%9910569.38%20421249.60%0.46%

    IAM1810681.69%3010562.84%4821242.26%-1.16%

    AVC1410681.31%510560.47%1921240.89%0.84%

    Muerte7910687.40%6910566.53%14821246.97%0.86%

    thetaVar(Th)Theta no sesgadoOR no sesgadoOR Z y Vdif (LS - LI)

    ZVZ/V1 / Vs2rWTh inssesgovar(Th ins)Th insLILSORLILSORLILSNo sesgZ y VU(normal)p[U(normal)]

    E-P-2.42446.102-0.0530.0221.0001.000?-0.1250.0730.028-0.125-0.4550.2040.8820.6341.2270.9490.7111.2660.5920.5550.74552802040.4559524323

    IAM6.13611.7290.5230.0850.2540.46610.8470.4560.0670.0910.456-0.1351.0471.5770.8732.8481.6870.9522.9901.9752.0381.5113184140.1307073932

    AVC-4.4464.708-0.9450.2120.1020.2914.294-1.0110.0660.218-1.011-1.926-0.0960.3640.1460.9080.3890.1580.9600.7630.8022.16561311680.0303406546

    Muerte-4.58234.422-0.1330.0290.7470.84033.446-0.2040.0710.035-0.204-0.5720.1640.8160.5641.1790.8750.6271.2230.6140.5961.08529282310.2777920559

    1.960.0499956504

    Theta^LILSTh insLILS

    E-PE-P-0.125-0.4550.204

    IAMIAM0.456-0.1351.047

    AVCAVC-1.011-1.926-0.096

    MuerteMuerte-0.204-0.5720.164

    ORLILSORLILS

    E-PAjustado0.8820.6341.227E-P0.8820.6341.227

    Crudo0.94878455490.71088766841.2662930751IAM1.5770.8732.848

    AVC0.3640.1460.908

    Ajustado1.5770.8732.848Muerte0.8160.5641.179

    Crudo1.6872861120.95200444422.9904633755

    Ajustado0.3640.1460.9080.94878455490.71088766841.2662930751

    Crudo0.38886693440.15757129340.9596766606

    Ajustado0.8160.5641.179

    Crudo0.87536805780.62676600141.2225762643

    Anlisis secundarios

    000

    000

    000

    000

    Th ins

    LI

    LS

    Theta~

    Estimacin p

    000

    000

    000

    000

    OR

    LI

    LS

    OR~

    000

    000

    000

    000

    000

    000

    000

    000

    000

    000

    000

    OR

    LI

    LS

    OR

    E = T(A)C = T(B)T

    nESEFEaEpEpEnCSCFCaCpCpCnSFp-p-p(dif)

    1Ej pg 90,152,1617151200.5110.7180.2826834340.48920.5000.50013985540.61150.3885-0.2183

    2Ej pg 90,152,1617151200.5110.7180.2826834340.48920.5000.50013985540.61150.3885-0.2183

    3E-P (M) Est10689631050.5030.9020.0981056957990.49720.9060.094212419202040.90400.09600.0046

    4E-P (M) LI10689631050.5030.9020.0981056957990.49720.9060.094212419202040.90400.09600.0046

    5E-P (M) LS10689631050.5030.9020.0981056957990.49720.9060.094212419202040.90400.09600.0046

    6E-P (~) Est10689631050.5030.9020.0981056957990.49720.9060.094212419202040.90400.09600.0046

    7E-P (~) LI10689631050.5030.9020.0981056957990.49720.9060.094212419202040.90400.09600.0046

    8E-P (~) LS10689631050.5030.9020.0981056957990.49720.9060.094212419202040.90400.09600.0046

    9IAM (~) Est10681050180.5030.9830.01710561026300.49720.9720.02821242076480.97740.0226-0.0116

    10IAM (~) LI10681050180.5030.9830.01710561026300.49720.9720.02821242076480.97740.0226-0.0116

    11IAM (~) LS10681050180.5030.9830.01710561026300.49720.9720.02821242076480.97740.0226-0.0116

    12AVC (~) Est10681054140.5030.9870.0131056105150.49720.9950.00521242105190.99110.00890.0084

    13AVC (~) LI10681054140.5030.9870.0131056105150.49720.9950.00521242105190.99110.00890.0084

    14AVC (~) LS10681054140.5030.9870.0131056105150.49720.9950.00521242105190.99110.00890.0084

    15Muerte (~) Est1068989790.5030.9260.0741056987690.49720.9350.065212419761480.93030.06970.0086

    16Muerte (~) LI1068989790.5030.9260.0741056987690.49720.9350.065212419761480.93030.06970.0086

    17Muerte (~) LS1068989790.5030.9260.0741056987690.49720.9350.065212419761480.93030.06970.0086

    ax2+bx+c=0 (x=p~c)T(B)T(A)

    ThetaaEaCp-e-th_ns(1-e-th_ns)abcp~cp~cp~Ep~Ep(dif)

    1Ej pg 90,152,161 (~)0.7990.5110.4890.6120.4500.5500.2690.394-0.2750.5160.4840.7030.297

    2Ej pg 90,152,161 (M)0.8970.5110.4890.6120.4080.5920.2900.348-0.2490.5050.4950.7140.286

    3E-P (M) Est-0.0860.5030.4970.9041.090-0.090-0.0451.127-0.9860.9089.23%90.02%9.98%0.75%

    4E-P (M) LI-0.4560.5030.4970.9041.578-0.578-0.2871.809-1.4260.9247.64%88.45%11.55%3.90%

    5E-P (M) LS0.2160.5030.4970.9040.8060.1940.0970.728-0.7280.89510.54%91.33%8.67%-1.87%

    6E-P (~) Est-0.1250.5030.4970.9041.134-0.134-0.0661.187-1.0250.9099.06%89.85%10.15%1.09%

    7E-P (~) LI-0.4550.5030.4970.9041.577-0.577-0.2871.808-1.4250.9247.64%88.46%11.54%3.90%

    8E-P (~) LS0.2040.5030.4970.9040.8150.1850.0920.741-0.7370.89510.49%91.28%8.72%-1.77%

    9IAM (~) Est0.4560.5030.4970.9770.6340.3660.1820.460-0.6200.9722.76%98.23%1.77%-0.99%

    10IAM (~) LI-0.1350.5030.4970.9771.145-0.145-0.0721.214-1.1190.9792.11%97.59%2.41%0.30%

    11IAM (~) LS1.0470.5030.4970.9770.3510.6490.3230.043-0.3430.9673.34%98.80%1.20%-2.14%

    12AVC (~) Est-1.0110.5030.4970.9912.748-1.748-0.8693.602-2.7240.9950.48%98.69%1.31%0.83%

    13AVC (~) LI-1.9260.5030.4970.9916.862-5.862-2.9149.724-6.8010.9980.23%98.45%1.55%1.32%

    14AVC (~) LS-0.0960.5030.4970.9911.101-0.101-0.0501.150-1.0910.9910.85%99.06%0.94%0.09%

    15Muerte (~) Est-0.2040.5030.4970.9301.226-0.226-0.1121.323-1.1410.9376.31%92.38%7.62%1.32%

    16Muerte (~) LI-0.5720.5030.4970.9301.772-0.772-0.3842.102-1.6490.9495.15%91.23%8.77%3.62%

    17Muerte (~) LS0.1640.5030.4970.9300.8480.1520.0750.784-0.7890.9257.50%93.56%6.44%-1.06%

  • Ejemplo monitorizacin Seguridad

  • References: BooksBooksWhitehead, J. (1997) The Design and Analysis of Sequential Clinical Trials. (Revised Second Edition). Chichester:Wiley

    Jennison C, Turnbull BW. Group Sequential Methods with Applications to Clinical Trials. Chapman & Hall/CRC: Boca Raton, 2000

  • References: SoftwareSoftware (1/2)

    CommercialPest v4. MPS research unit, University of Readinghttp://www.rdg.ac.uk/mps/mps_home/software/pest4/pest4.htmEaSt 2000. Cytel Software Corporation.http://www.cytel.com/new.pages/EAST.2.htmlS-PLUS. S+ SeqTrialhttp://www.insightful.com/products/product.asp?PID=16

  • ReferencesSoftware (2/2)

    FreePrograms for Computing Group Sequential BoundariesUsing the Lan-DeMets Method. Version 2.1. David M. Reboussin, David L. DeMets, KyungMann Kim, K. K. Gordon Lanhttp://www.medsch.wisc.edu/landemets/Experiments and clinical trials in medicine: Computer programs enabling clinicians to design group sequential experiments (Repeated significance tests - R.S.T. - experiments). MEDSEQ by By Egil H. Lehmann and Hogne Sandvik.http://www.uib.no/isf/medseq.htmChristopher Jennison.http://www.bath.ac.uk/~mascj/book/programs/general

  • References: Some published Clinical Trials

    The Triangular Test (1/2)Anaesthesia for outpatient termination of pregnancy. Hackett et al. (1982). British Journal of Anaesthesia, 54, 865-870Immunotherapy regimens in bone marrow transplantation for leukaemia. Storb et al. (1986). New England Journal of Medicine, 314, 729-735Corticosteroids in AIDS-induced pneumonia. Montaner et al. (1990) Annals of Internal Medicine, 113, 4-20Insulin and glucagon in severe alcoholic hepatitis. Trinchet et al. (1992). Hepatology, 15, 76-81Enoxaparin in deep vein thrombosis resulting from hip replacement surgery. Whitehead (1992). Pharmaceutical Medicine, 6, 179-191Cisplatin in limited small-cell lung cancer. Arriagada et al. (1993). New England Journal of Medicine, 329, 1848-1852Spinal anaesthesia during Caesarian section (in a design also using the play-the -winner rule). Rout et al. (1993). Anaesthesiology, 79, 262-269Isradipine in stroke. Whitehead (1993). Drug Information Journal, 27, 733-740Surfactant in infantile respiratory distress. Gortner et al. (1994). Acta Paediatrica, 83, 135-141

  • References: Some published Clinical Trials

    The Triangular Test (2/2)Lipiodol chemoembolisation in hepatocellular carcinoma. Group d'Etude et Traitement du Carcinoma Hepatocellulaire. (1995). New England Journal of Medicine, 332, 1256-1261Defibrillators in coronary heart disease. Moss et al. (1996). New England Journal of Medicine, 335, 1933-1940Somastatin in acute oesophageal variceal bleeds. Avegerinos et al. (1997). The Lancet, 350, 1495-1499Metoclopramide in gastroesophageal reflux. Bellissant et al. (1997). Clinical Pharmacology and Therapeutics, 61, 377-384Viagra in erectile dysfunction. Derry et al. (1997). Neurology, 51, 1629-1633Interferon and cytarabine in chronic myelogenous leukaemia. Guilhot et al. (1997). New England Journal of Medicine, 337, 223-239Alpha-interferon in renal cancer. MRC Renal Cancer Collaborators (1999). The Lancet, 353, 14-17Electrical defibrillation in an animal model of vertriacular fibrillation. Niemann et al. (2000). Journal of the American College of Cardiology, 36, 932-938Lenograstim in leukaemia. Bradstock et al. (2001). Leukemia, 15, 1331-1338

  • References: Some published Clinical Trials

    The Double Triangular Test Comparison of theatre mattresses in respect of pressure sore incidence during surgery. Nixon et al. (1998). International Journal of Nursing Studies, 35, 193-203 Brown et al. (2000). Statistics in Medicine, 19, 3389-3400Diltiazem in acute myocardial infarction. Boden et al. (2000). The Lancet, 355, 1751-1756Glycopyrolate in elective Caesarian section. Yentis et al. (2000). International Journal of Obstetric Anaesthesia, 9, 156-159Chemotherapy in high-risk breast cancer. Bergh et al. (2000). The Lancet, 356, 1384-1391Thromboembolism during hormone replacement therapy. Hoibraaten et al. (2000). Thrombosis and Haemostasis, 84, 961-967Remacamide and carbamazepine in newly diagnosed epilepsy. Whitehead (2001). Epilepsy Research, 45, 81-87Lithium gamolenate in pancreatic cancer. Johnson et al. (2001). British Journal of Surgery, 88, 662-668Reliability of contrast agents in assessing the potency of Fallopian tubes. Boudghene (2001). Ultrasound Obstet. Gynecol., 18, 525-530

  • References: Some published Clinical Trials

    The Double Truncated SPRT Comparison of triflusal with aspirin following acute myocardial infarction. Cruz-Fernandez et al. (2000). European Heart Journal, 21, 457-465The Restricted Procedure Tiaprofenic acid and indomethacin in osteoarthritis. Whitehead and Thomas (1997). Journal of Biopharmaceutical Statistics, 7, 333-353Safety Monitoring Examples for severe head injury, stroke and heart disease. Bolland and Whitehead (2000). Statistics in Medicine, 19, 2899-2917Open Top DesignRilozole in amyotrophic lateral sclerosis. Lacomblez et al. (1996). The Lancet, 347, 1425-1431

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