Presentation on theme: "1 Using an External Control to Evaluate the Effectiveness of Posaconazole for Refractory Invasive Fungal Infections Kenneth J. Koury Jagadish P. Gogate."— Presentation transcript:
1 Using an External Control to Evaluate the Effectiveness of Posaconazole for Refractory Invasive Fungal Infections Kenneth J. Koury Jagadish P. Gogate Schering-Plough Research Institute
2 Refractory Invasive Fungal Infections (rIFI) Life-threatening infections Limited therapeutic options, especially in salvage setting Randomized study –straightforward interpretation of results –not practical to complete in a timely fashion –serious ethical issue: potential enrollment of subjects into a failing regimen No randomized trials completed for salvage therapy for any antifungal drug
3 Description of Study P00041 Open-label, non-randomized, multinational, salvage therapy study Posaconazole oral suspension 400 mg bid Subjects with invasive fungal infections refractory to standard antifungal therapies or subjects who were intolerant of standard antifungal agents Started In January 1999 (compassionate use) Enrollment expanded based on investigator interest, completed by April 2001
4 Advice from Regulatory Authorities CPMP (Committee for Proprietary Medicinal Products) –lack of randomized trial always makes it difficult to evaluate a new agent –well-conducted external-control study may provide a useful comparative reference –sponsor must demonstrate that any potential selection bias was minimized –show that two groups are clinically similar
5 Advice from Regulatory Authorities FDA –treatment for rIFI may fulfill an unmet medical need –response rates from a control group required –numerous discussions regarding design and analysis of external-control study (P02387) comparability of patient populations minimization of potential bias
6 External-Control Study (P02387) Provide reference (benchmark) for comparison to P00041 Procedures and methods prospectively implemented to minimize potential sources of bias Exhaustive review of all cases of IFI at study centers over target time period –2073 screened for possible enrollment –279 fulfilled criteria
7 Control of Potential Bias External Data Review Committee (DRC) –15 independent clinical experts and 2 radiologists –Concurrent, blinded review of data from 330 posaconazole-treated subjects (P00041) and 279 external-control subjects (P02387) –Determined patient eligibility met MSG/EORTC criteria for proven or probable IFI met criteria for refractory disease or intolerance of standard therapy or both –Determined patient outcome: global response status at end of treatment
8 Selection Bias Exhaustive review of all cases of IFI at study centers during comparable time period Similar inclusion and exclusion criteria Autopsy data not used for identifying control subjects Exclude control subjects who died within 72 hours of after the initiation of therapy
9 Information Bias Inherent differences in the amount of data available in a retrospective study vs. prospective study Develop uniform format for data presentation to maintain blinding of DRC Outcome data from a given subject are not available for review by DRC until eligibility of that subject has been determined
10 Temporal and Geographic Bias Use same time frame (almost concurrent rather than historical controls) Use mostly same centers Expect controls to have similar disease characteristics to posaconazole-treated subjects
11 Other Important Factors Primary pathogen (type of fungus) Infection site Underlying disease and associated treatments –BMT, Solid Organ Transplant –Hematologic malignancies –HIV/Aids –Use of immune response modifiers, growth factors
12 Baseline and Disease Characteristics (With Potential to Influence Outcome) Demographic Variables: Age, Gender, Race and Weight. Refractory Status Intolerance Status Period of Enrollment Primary Pathogen: Aspergillus, Candida and Other Yeast, Fusarium, Cryptococcus, Zygomycetes, Other Filamentous Fungi, Other Endemic Fungi and Multiple Pathogens Infection Site: pulmonary, extra pulmonary, disseminated with pulmonary involvement and disseminated without pulmonary involvement
13 Baseline and Disease Characteristics (With Potential to Influence Outcome) Underlying Disease [9 variables each with two categories (present and absent]: Hematologic Malignancies, Non-Hematologic Malignancies, Nonmalignant Hematologic Disorders, Bone Marrow Transplant, Solid Organ Transplant, Renal Disease, Hepatic Disease, Immunocompromised- Acquired, Immunocompromised-Congenital Duration of prior effective antifungal therapy. Baseline Neutropenia Prior systemic corticosteroid use and Concurrent systemic corticosteroid use
14 Primary Efficacy Endpoint DRC-adjudicated Global Response Status at the end of treatment – subject considered a responder if global response at EOT was classified as a complete or partial response –subject considered a non-responder if classified as stable disease, failure, or unable to determine
15 Global Response Status Complete Response – Resolution of all attributable clinical signs and symptoms, radiological and mycological abnormalities, if present at baseline. Partial Response –Clinically meaningful improvement in attributable clinical signs and symptoms, radiological and mycological abnormalities, if present at baseline. Stable Disease –No improvement in attributable clinical signs symptoms, radiological and mycological abnormalities, if present at baseline Failure –Deterioration in attributable clinical signs and symptoms, radiological and/or mycological abnormalities necessitating alternative antifungal therapy or resulting in death Unable to Determine –If for any reason the global response cannot be assessed (e.g., insufficient medical records to determine outcome)
16 Primary Analysis Modified ITT Population –subjects with proven or probable aspergillosis –refractory to standard therapy or intolerant Analysis of Global Response Rate –Logistic regression model includes: treatment key prognostic factors other potential prognostic factors (with treatment imbalances at baseline) –Assessment of treatment differences based on odds ratio for treatment effect and its 95% confidence interval
17 Prognostic Variables Key Variables Refractory status Intolerance status Site of infection Presence of baseline neutropenia Duration of prior antifungal therapy Region Other Variables All other baseline and disease characteristics considered as potential prognostic variables Included as covariates in primary statistical analysis if treatment imbalance at baseline is significant (p<0.10)
18 Supportive Analyses Two step procedure Preliminary analysis to identify prognostic indicators with potential to influence global response –Based on a logistic regression procedure –All variables (except treatment) included –Variable selection option STEPWISE in PROC LOGISTIC of SAS (significance level 0.15 for entry and 0.10 for stay) Statistical Modeling –Logistic regression on global response with treatment and other covariates selected from the above procedure.
19 Secondary Analyses Survival Analyses Time to Death (logrank test) Cox Proportional Hazards Model –Treatment Group –Site of Infection –Refractory Status, Intolerance Status –Baseline Neutropenia
20 Additional Analyses Forming cohorts based on a Prognosis Score (low, intermediate, high risk) Use of Propensity scores
21 Baseline and Disease Characteristics
22 Baseline and Disease Characteristics
23 Baseline Comparisons Both studies are comparable with respect to the distribution of demographic and almost all of the baseline disease characteristics Majority of the subjects are refractory to prior antifungal therapies Study P00041 has generally sicker patients (e.g., hepatic disease and renal disease)
25 Primary Efficacy Analysis Logistic Regression on Global Response Key Prognostic Factors included –Refractory Status, Intolerance Status, Site of Infection, Neutropenia, Duration of Prior Antifungal Therapy, Age and Region of Enrollment. Potential Prognostic Factors with Baseline Imbalance –Enrollment Time, Race, Non-malignant Hematologic Disorders, Renal Disease and Hepatic Disease
26 Results of Primary Efficacy Analysis Only two significant variables in the model –Treatment and Baseline Neutropenia –No interaction between Treatment and Neutropenia based on a logistic regression model with Treatment, Neutropenia and interaction between them Odds Ratio for Treatment: 4.06 P-value for the Treatment Effect: % Confidence Interval: (1.50, 11.04)
27 Impact on Odds Ratio for Treatment Effect Sequential Addition of Prognostic Variables Variable Added in the Model Sequentially Odds RatioP-value No covariate Neutropenia Region Hepatic Disease Refractory Status Intolerance Status Infection Site Non-malignant Hematologic Disorders Age Renal Disease Prior AF duration Enrollment Time Race Group
28 Supportive Analysis Variables associated with the Global Response selected using the Stepwise Logistic Regression –Baseline Neutropenia, Prior Corticosteroid Use, Solid Organ Transplant Logistic regression on Global Response with Treatment and the above variables in the Model Odds Ratio for Treatment: 2.05 P-value for the Treatment Effect: Confidence Interval: (1.06, 3.97)
29 Sensitivity Analyses No.Variations of the Prognostic FactorsORCI/P-value 1Excluded Non-malignant Hematologic Disorders, Renal and Hepatic Disease 2.68(1.15, 6.27)/ Binary infection site, Continuous Age and Prior AF duration 3.67(1.41, 9.54)/ Binary Enrollment and Infection site, Continuous Age and Ordinal Prior AF duration 3.73(1.51, 9.21)/ Binary Enrollment and Infection Site, Continuous Age and Prior AF duration 3.45(1.42, 8.41)/ Ordinal Enrollment, Binary Infection site, Continuous Age and Ordinal Prior AF duration 3.48(1.39, 8.72)/ Ordinal Enrollment, Binary Infection site, Binary Prior AF duration ( 30) and Continuous Age 3.69(1.46, 9.35)/0.006
30 Global Response Rates by Baseline Neutropenia Study protocol P00041P02387 N%N% Neutropenia Status: 1/333.3 Missing Neutropenia5/ /267.7 No Neutropenia35/ / Unable to Determine4/580.01/250.0 Total45/ /8625.6
31 Global Response Rates by Corticosteroid Use Study protocol P00041P02387 N%N% Prior Corticosteroid: 15/ / No prior use Prior use30/ / Concomitant Corticosteroid: 13/ / No Concomitant use Concomitant use32/ / Total45/ /8625.6
32 Global Response Rates by Infection Site Study protocol P00041P02387 N%N% Infection Site Pulmonary31/ / Extra-Pulmonary10/ / Disseminated with Pulmonary Involvement 1/333.30/30 Disseminated w/o Pulmonary Involvement 3/6500/50 Total45/ /8625.6
33 Global Response Rates by Underlying Disease Conditions Study protocol P00041 (n=107) P02387 (n=86) N%N% Bone Marrow Transplant21/ / Solid Organ Transplant7/ /771.4 Hematologic Malignancies29/ / Non-malignant Hematologic Disorders 36/ / Non-hematologic malignancies6/ /520.0 Immunosuppressive-acquired13/ / Immunosuppressive-congenital1/250.00/30.0 Renal Disease27/ / Hepatic Disease16/ /60.0 No Identifiable Risk Factors1/1100.0
35 Variables used for Prognosis Score BMT, Solid Organ Transplant, Acquired Immunodeficiency, Congenital Immunodeficiency, Hematologic Malignancy, Non-hematologic Malignancy, Non-malignant Hematologic Disorder, Renal disease risk factor OR Creatinine >= Grade 1, Liver disease risk factor OR Total Bilirubin >= Grade 1 OR SGOT >= Grade 1 OR SGPT >= Grade 1, Prior Systemic Steroid use, Prior Immunosuppressive therapy, Prior Myelosuppressive therapy, Baseline Neutropenia, Baseline Mechanical Ventilation, and Baseline GVHD Prognosis Score: one point added to subjects score for each condition that is present
36 Global Response Rate by Prognosis Score Prognosis Score GroupP00041 Posaconazole P02387 Control Low Risk (0-1)2/2 (100%)- Intermediate Risk (2-4)10/21 (58%)8/25 (32%) High Risk (>=5)33/48 (39%)14/61 (23%) All45/107 (42%)22/86 (26%) P-value = based on CMH stratified analysis for general association.
37 Propensity Scores Propensity Score is defined as the conditional probability of being treated given the covariates. Estimated propensity score can be used to reduce the bias through matching, stratification, regression adjustment or some combination of all three. Advantage of using propensity scores in estimating treatment effect is its simplicity in interpreting the results. Quantiles of the distribution of the propensity scores can be used as covariates in logistic regression analysis or as strata in assessing the treatment effect.
38 Global Response Rate by Propensity Score Group Propensity Score Group P0041P02387 <=0.1770/1 (0%)18/57(32%) <= /16 (63%)3/18 (17%) <= /33 (36%)1/9 (11%) > /57 (40%)0/2 (0%) All45/107 (42%)22/86 (26%) P-value using the logistic regression is P value based on the CMH analysis is
39 Summary and Conclusions Posaconazole is substantially more effective than control for treatment of rIFI due to aspergillus The adjusted odds ratio obtained from the primary analysis is almost twice as large as the unadjusted odds ratio The treatment effect based on primary analysis is robust in the sense that it is not sensitive to the classification of baseline and disease characteristics used to specify the way in which the prognostic factors were incorporated in the analyses.
40 Summary and Conclusions The treatment effect is statistically significant even when the influential factors non-malignant hematologic disorders, hepatic disease and renal disease are excluded from the primary model (odds ratio=2.70, p-value=0.0227). Alternate methods of controlling for prognostic factors confirm effectiveness of posaconazole. Survival (based on the Kaplan-Meier estimates) is substantially longer in subjects treated with Posaconazole than control subjects. Kaplan-Meier estimates of the survival rates at the end of one year are 38 % and 22% in P0041 and P02387 respectively.