Model-Based Prediction of Phase III Overall Survival in Colorectal Cancer on the Basis of Phase II Tumor Dynamics

2009 ◽  
Vol 27 (25) ◽  
pp. 4103-4108 ◽  
Author(s):  
Laurent Claret ◽  
Pascal Girard ◽  
Paulo M. Hoff ◽  
Eric Van Cutsem ◽  
Klaas P. Zuideveld ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Time ◽  
Phase Ii ◽  
Tumor Size ◽  
Prediction Interval ◽  
Phase Iii ◽  
Antitumor Response ◽  
Phase Iii Study ◽  
Phase Iii Studies ◽  
Size Data

PurposeWe developed a drug-disease simulation model to predict antitumor response and overall survival in phase III studies from longitudinal tumor size data in phase II trials.MethodsWe developed a longitudinal exposure-response tumor-growth inhibition (TGI) model of drug effect (and resistance) using phase II data of capecitabine (n = 34) and historical phase III data of fluorouracil (FU; n = 252) in colorectal cancer (CRC); and we developed a parametric survival model that related change in tumor size and patient characteristics to survival time using historical phase III data (n = 245). The models were validated in simulation of antitumor response and survival in an independent phase III study (n = 1,000 replicates) of capecitabine versus FU in CRC.ResultsThe TGI model provided a good fit of longitudinal tumor size data. A lognormal distribution best described the survival time, and baseline tumor size and change in tumor size from baseline at week 7 were predictors (P < .00001). Predicted change of tumor size and survival time distributions in the phase III study for both capecitabine and FU were consistent with observed values, for example, 431 days (90% prediction interval, 362 to 514 days) versus 401 days observed for survival in the capecitabine arm. A modest survival improvement of 39 days (90% prediction interval, −21 to 110 days) versus 35 days observed was predicted for capecitabine.ConclusionThe modeling framework successfully predicted survival in a phase III trial on the basis of capecitabine phase II data in CRC. It is a useful tool to support end-of-phase II decisions and design of phase III studies.

Model-based predictions of expected anti-tumor response and survival in phase III studies based on phase II data of an investigational agent

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6025-6025 ◽  
Author(s):  
L. Claret ◽  
P. Girard ◽  
J. O’shaughnessy ◽  
P. Hoff ◽  
E. Van Cutsem ◽  
...  
Keyword(s):  
Survival Time ◽  
Clinical Response ◽  
Phase Ii ◽  
Tumor Size ◽  
Tumor Response ◽  
Survival Model ◽  
Phase Iii ◽  
Alternative Methods ◽  
Phase Ii Trials ◽  
Phase Iii Studies

6025 Background: Decision making during early oncology drug development remains very empirical. A drug-disease simulation model to predict expected clinical response and survival in phase III studies from observed longitudinal tumor size in phase II trials offers a science-based alternative. Methods: We developed the following: 1) longitudinal exposure-response models of drug effect (and resistance) on tumor growth dynamics based on phase II data on capecitabine (X) in metastatic breast (MBC) and colorectal cancer (MCRC) and on historical phase III data on docetaxel (T) in MBC and 5-FU in MCRC; and 2) a survival model relating change in tumor size and patient characteristics to survival time in MBC and MCRC based on phase III data. The models were validated and used to predict expected anti-tumor response and survival in phase III studies of XT vs. T alone in MBC and X vs. 5-FU in MCRC. Multiple replicates (n = 1000) of simulated phase III studies were compared to actual results. Results: Change of tumor size and survival time distributions in X arms were well predicted. In MBC, expected median (90% prediction interval) survival for patients treated with XT was 412 (range 330 to 526) days (vs. 431 days observed) with an improvement over T of 57 days (range -17 to 148) (vs. 78 days observed). For MCRC patients, X treatment resulted in a potential survival improvement of 39 (range -21 to 110) days (vs. 35 days observed) compared to patients treated with 5-FU. Conclusions: The dose-tumor size-survival model succeeded in predicting survival in phase III trials based on X phase II data in MBC (in combination with T) and as a single agent in MCRC. This model is a useful tool to compare expected clinical response of new compounds to various competitors and to support end-of-phase II decisions and design of phase III studies. [Table: see text]

Evaluation of Tumor-Size Response Metrics to Predict Overall Survival in Western and Chinese Patients With First-Line Metastatic Colorectal Cancer

2013 ◽  
Vol 31 (17) ◽  
pp. 2110-2114 ◽  
Author(s):  
Laurent Claret ◽  
Manish Gupta ◽  
Kelong Han ◽  
Amita Joshi ◽  
Nenad Sarapa ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Tumor Size ◽  
Prediction Interval ◽  
Phase Iii ◽  
Chinese Patients ◽  
First Line ◽  
Two Phase ◽  
Chinese Ethnicity ◽  
Phase Iii Studies

PurposeTo assess new metrics of tumor-size response to predict overall survival (OS) in colorectal cancer (CRC) in Western and Chinese patients.Patients and MethodsVarious metrics of tumor-size response were estimated using longitudinal tumor size models and data from two phase III studies that compared bevacizumab plus chemotherapy versus chemotherapy as first-line therapy in Western (n = 923) and Chinese (n = 203) patients with CRC. Baseline prognostic factors and tumor-size metrics estimates were assessed in multivariate models to predict OS. Predictive performances of the models were assessed by simulating multiple replicas of the phase III studies.ResultsTime to tumor growth (TTG) was the best metric to predict OS. TTG fully captured bevacizumab effect. Chinese ethnicity had no impact on OS or on the TTG-OS relationships. The model correctly predicted OS distributions in each arm as well as bevacizumab hazard ratio (model prediction, 0.75 v 0.68 observed in Western patients; 95% prediction interval, 0.62 to 0.91).ConclusionTTG captured therapeutic benefit with bevacizumab in first-line CRC patients. Chinese ethnicity had no impact. Longitudinal tumor size data coupled with model-based approaches may offer a powerful alternative in the design and analysis of early clinical studies.

Evolution of statistical methodology and design of phase II/III clinical trials in non-small cell lung cancer (NSCLC)

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 7108-7108 ◽  
Author(s):  
R. K. Bagai ◽  
A. Dowlati
Keyword(s):  
Clinical Trials ◽  
Survival Time ◽  
Phase Ii ◽  
Response Rate ◽  
Phase Iii ◽  
Type I ◽  
Phase Ii Trials ◽  
Improvement In Survival ◽  
Phase Ii And Iii ◽  
Phase Iii Studies

7108 Background: A significant heterogeneity exists in the design and reporting of phase II and III therapeutic clinical trials in NSCLC. This has led to difficulty in interpretation of these trials leading to over- or underestimation of therapeutic efficacy. We set out to investigate the statistical methodology and design reporting of chemotherapeutic trials in NSCLC published in the Journal of Clinical Oncology (JCO) over 20 years. Methods: We identified all phase II and III NSCLC chemotherapy trials published in the JCO from January 1983 to August 2005. All manuscripts were reviewed to evaluate components of statistical design that were reported, including: sample size calculation, power, type I error, single or multiple drug trials, relative response sought in phase II trials and improvement in survival time or response rate sought in phase III trials. Results: One hundred forty eight trials were identified. 52% of studies were phase III and 48% were phase II. The majority (78%) were conducted in advanced stage NSCLC. Sample size calculations were reported for only 58% of phase III studies and 31% of phase II studies. Power was reported in 66% of phase III studies and 13% of phase II trials. Type I error was reported in 47% of phase III studies and 17% in phase II studies. 60% of phase III trials defined endpoints (percentage improvement in survival time, improvement in survival time in months or increase in response rate). 41% of phase II trails defined the target response rate, ranging from response rates of 15% to 70%. The frequency of adequate reporting of statistical design was shown to increase from 31% in 1990–1995 to 64% in 2000–2005 ( table ). Conclusions: Significant heterogeneity exists in trial design and reporting of phase II and III trials in NSCLC. This impacts the ability to adequately interpret these studies. More widespread application of statistical methods in planning and reporting of lung cancer clinical trials are necessary to increase reliability of data. [Table: see text] No significant financial relationships to disclose.

Results of the X-PECT study: A phase III randomized double-blind, placebo-controlled study of perifosine plus capecitabine (P-CAP) versus placebo plus capecitabine (CAP) in patients (pts) with refractory metastatic colorectal cancer (mCRC).

2012 ◽  
Vol 30 (18_suppl) ◽  
pp. LBA3501-LBA3501 ◽  
Author(s):  
Johanna C. Bendell ◽  
Thomas J. Ervin ◽  
Neil N. Senzer ◽  
Donald A. Richards ◽  
Irfan Firdaus ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Phase Ii ◽  
Median Overall Survival ◽  
Phase Iii ◽  
Controlled Study ◽  
Double Blind ◽  
Double Blind Placebo ◽  
Randomized Phase Ii ◽  
Phase Iii Study

LBA3501 Background: Perifosine (P) is an oral, synthetic alkylphospholipid that inhibits or modifies signal transduction pathways including AKT, NFkB and JNK. A randomized phase II study examined P-CAP vs. CAP in pts with 2nd or 3rd line mCRC. This study showed improvement in mTTP (HR 0.254 [0.117, 0.555]) and mOS (HR 0.370 [0.180,0.763]). Based on these results, a randomized phase III study of P-CAP vs. CAP with a primary endpoint of overall survival (OS) in pts with refractory mCRC was initiated. Methods: The study was a prospective, randomized, double-blind, placebo-controlled randomized phase III trial. Eligible pts had mCRC which was refractory to all standard therapies. Pts randomized 1:1 to Arm A = P-CAP (P 50 mg PO QD + CAP 1000 mg/m2PO BID d1-14) or Arm B = CAP (placebo + CAP 1000 mg/m2 PO BID d 1-14). Cycles were 21 days. Baseline tumor block collection and a biomarker cohort of pts with pre- and on-treatment tumor and blood samples were performed. Results: Between 3/31/10 and 8/12/11, 468 pts were randomized, 234 pts were in each arm. Baseline demographics were balanced between the arms: age < 65y (A: 65%, B: 58.5%), male (A: 57.7%, B: 53.0%), ECOG PS 0 (A: 39.7%, B: 39.7%), K-ras mutant (A: 50.4%, B: 51.3%), and median number of prior therapies (A: 4, B: 4). As of 3/19/12, median follow up was 6.6 months. Median overall survival: Arm A = 6.4 mo, Arm B = 6.8 mo, HR 1.111 [0.905,1.365], p = 0.315. Median overall survival for K-ras WT pts: Arm A = 6.6 mo, Arm B = 6.8 mo, HR 1.020 [0.763,1.365], p = 0.894; K-ras mutant pts: Arm A = 5.4 mo, Arm B = 6.9 mo HR 1.192 [0.890,1.596], p = 0.238. Conclusions: Despite promising randomized phase II data, this phase III study shows no benefit in overall survival adding perifosine to capecitabine in the refractory colorectal cancer setting. Response rate, progression free survival, and safety data will be presented. Biomarker analysis is pending to see if subgroups of patients may have potential benefit.

Model-based estimates of tumor growth inhibition (TGI) metrics to predict for overall survival (OS) in first-line non-small cell lung cancer (NSCLC).

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e19049-e19049 ◽  
Author(s):  
Laurent Claret ◽  
Pierre Mancini ◽  
Bernard Sebastien ◽  
Christine Veyrat-Follet ◽  
Rene Bruno
Keyword(s):  
Tumor Growth ◽  
Phase Ii ◽  
Tumor Size ◽  
Univariate Analysis ◽  
External Validation ◽  
Phase Iii ◽  
Parameter Estimates ◽  
Ratio Test ◽  
Phase Ii Studies ◽  
Phase Iii Study

e19049 Background: A survival model using change in tumor size at week 8 from baseline (CTS) (Clin Pharmacol Ther 86:167-174, 2009) was used to predict OS of the motesanib phase III study in NSCLC (Clin Pharmacol Ther 92:631-634, 2012). However CTS may not fully capture treatment effect on OS. We investigated other TGI metrics to predict OS using historical phase III data. Methods: Various TGI metrics, CTS, time to growth (TTG), and tumor growth rate (G), were estimated using two longitudinal tumor size models (Clin Cancer Res 17:907-917, 2011, PAGE 21 [www.page-meeting.org/?abstract=2328], 2012, JCO in press, 2013) developed from phase III data (1218 1st-line patients with NSCLC treated with doxetaxel (D) plus cisplatin (Cs) or carboplatin (Cb) or vinorelbine (V) plus Cs) (J Clin Oncol, 21:2016-3024, 2003). TGI metrics and baseline prognostic factors were assessed in univariate Cox and multivariate parametric survival models. Alternative models were qualified by simulating OS distributions in 1000 replicates of the phase III study and checking that observed OS distribution belongs to the 95% prediction intervals. Results: In a univariate analysis all TS metrics were strong predictors of OS (p<0.0001). TTG and G were similar and much better than CTS (likelihood ratio test). OS was best described by a log-normal distribution and the influence of the covariates was assessed based on linear regression of the logarithm of OS (days). Parameter estimates of the best multivariate model are shown in the Table. The model was qualified in predicting OS distributions in the 3 arms (D+Cs, D+Cb, V+Cs). Conclusions: With further external validation, this model could be used to analyze longitudinal NSCLC tumor size data and their relationship to OS, in phase II studies of new agents and support end-of-phase-II decisions. [Table: see text]

Comparison of Outcomes of Phase II Studies and Subsequent Randomized Control Studies Using Identical Chemotherapeutic Regimens

2005 ◽  
Vol 23 (28) ◽  
pp. 6982-6991 ◽  
Author(s):  
Mohammad I. Zia ◽  
Lillian L. Siu ◽  
Greg R. Pond ◽  
Eric X. Chen
Keyword(s):  
Phase Ii ◽  
English Language ◽  
Response Rates ◽  
Phase Iii ◽  
Positive Phase ◽  
Phase Ii Studies ◽  
Solid Malignancies ◽  
Study Characteristics ◽  
Phase Iii Study ◽  
Phase Iii Studies

Purpose To determine whether promising results from phase II studies could be reproduced in phase III studies, and to examine which characteristics of phase II studies might be of predictive value for subsequent phase III studies. Methods We searched for all phase III studies of chemotherapy in advanced solid malignancies, published in the English language literature from July 1998 to June 2003. Each phase III study was reviewed to identify preceding phase II studies. Phase II and phase III studies included in this analysis must have used identical regimens. Data were extracted from both phase II and phase III studies. Results Of 181 phase III studies identified, 43 used therapeutic regimens identical to those in 49 preceding phase II studies. Twelve phase III studies (28%) were “positive.” The vast majority (81%) of phase III studies have lower response rates than preceding phase II studies, with a mean difference of 12.9% among all studies analyzed. None of the phase II study characteristics evaluated significantly predicted for “positive” phase III studies, but the sample size of phase II studies demonstrated a trend toward being predictive (P = .083). Conclusion Promising results from phase II studies frequently do not translate into “positive” phase III studies. Response rates in most phase III studies are lower than those in preceding phase II studies.

Simulation of survival with first- and second-line non-small cell lung cancer (NSCLC) therapy using a public domain drug-disease modeling framework

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 8087-8087
Author(s):  
R. Bruno ◽  
J. Lu ◽  
Y. Sun ◽  
L. Claret
Keyword(s):  
Phase Ii ◽  
Tumor Size ◽  
Tumor Response ◽  
Disease Modeling ◽  
Prediction Interval ◽  
Performance Status ◽  
Phase Iii ◽  
Second Line ◽  
Survival Times ◽  
Modeling Framework

8087 Background: Modeling and simulation approaches are advocated to support drug development decisions. In this study, we evaluated the ability of a drug-disease model recently developed by scientists at the FDA using data from pivotal studies in NSCLC (Wang et al. http://www.fda.gov/ohrms/dockets/ac/08/briefing/2008–4351b1–00-index.htm ) to simulate survival and tumor response for approved therapies in NSCLC. Methods: The modeling framework comprises a longitudinal tumor size model and a survival model relating change in tumor size at first visit (week 8) and patient characteristics (tumor size and ECOG performance status at baseline) to survival time. The tumor size and survival models were used to simulate change in tumor size at first visit and expected survival in the carboplatin/paclitaxel (CP) arm of the E4599 study (first-line NSCLC, N Eng J Med. 2006;355:2542–2550) and in the erlotinib arm in the BR.21 study (second-line NSCLC, N Eng J Med. 2005;353:123–132). The predictive distributions (95% prediction interval [PI]) of survival times were derived from multiple replicates (500) of 400 CP patients and 500 erlotinib patients with similar characteristics to patients in the original studies. Results: There was a high level of concordance between the results of the simulation and the observed results in the two arms, indicating that the modeling framework successfully predicted survival and tumor response. Expected median survival was 9.8 (95% PI, 8.2–11.8) months (vs 10.3 months observed) for the CP arm and 6.8 (95% PI, 5.3–8.9) months (vs 6.7 months observed) for the erlotinib arm. The median change in relative tumor size from baseline at week 8 predicted by the model was 12.1% for the CP arm and 9.5% for the erlotinib arm. Conclusions: The modeling framework can be used to perform simulations of survival of approved treatments. These results suggest that the model could be used to simulate survival for investigational treatments based on tumor shrinkage data observed in early clinical studies (e.g. phase II) to support end-of-phase II decisions and the design of phase III studies. [Table: see text]

scholarly journals Using phase II data for the analysis of phase III studies: An application in rare diseases

2017 ◽  
Vol 14 (3) ◽  
pp. 277-285 ◽  
Author(s):  
Simon Wandel ◽  
Beat Neuenschwander ◽  
Christian Röver ◽  
Tim Friede
Keyword(s):  
Drug Development ◽  
Phase Ii ◽  
Interim Analysis ◽  
Large Scale ◽  
Drug Approval ◽  
Phase Iii ◽  
Orphan Diseases ◽  
Operating Characteristics ◽  
Phase Iii Study ◽  
Phase Iii Studies

Background: Clinical research and drug development in orphan diseases are challenging, since large-scale randomized studies are difficult to conduct. Formally synthesizing the evidence is therefore of great value, yet this is rarely done in the drug-approval process. Phase III designs that make better use of phase II data can facilitate drug development in orphan diseases. Methods: A Bayesian meta-analytic approach is used to inform the phase III study with phase II data. It is particularly attractive, since uncertainty of between-trial heterogeneity can be dealt with probabilistically, which is critical if the number of studies is small. Furthermore, it allows quantifying and discounting the phase II data through the predictive distribution relevant for phase III. A phase III design is proposed which uses the phase II data and considers approval based on a phase III interim analysis. The design is illustrated with a non-inferiority case study from a Food and Drug Administration approval in herpetic keratitis (an orphan disease). Design operating characteristics are compared to those of a traditional design, which ignores the phase II data. Results: An analysis of the phase II data reveals good but insufficient evidence for non-inferiority, highlighting the need for a phase III study. For the phase III study supported by phase II data, the interim analysis is based on half of the patients. For this design, the meta-analytic interim results are conclusive and would justify approval. In contrast, based on the phase III data only, interim results are inconclusive and require further evidence. Conclusion: To accelerate drug development for orphan diseases, innovative study designs and appropriate methodology are needed. Taking advantage of randomized phase II data when analyzing phase III studies looks promising because the evidence from phase II supports informed decision-making. The implementation of the Bayesian design is straightforward with public software such as R.

Phase II clinical study of combination therapy with irinotecan and S-1(IRIS) for inoperable recurrent advanced colorectal cancer (2nd report): For Hokkaido Gastrointestinal Cancer Study Group (HGCSG)

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 4105-4105
Author(s):  
Y. Komatsu ◽  
S. Yuki ◽  
I. Iwanaga ◽  
M. Kudo ◽  
M. Tateyama ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Clinical Study ◽  
Combination Therapy ◽  
Survival Time ◽  
Phase Ii ◽  
Advanced Colorectal Cancer ◽  
High Response Rate ◽  
Phase Iii ◽  
Outpatient Basis ◽  
Phase Ii Clinical Study

4105 Background: We planned to conduct a phase II clinical study of combination therapy with irinotecan and S-1, a new oral anticancer drug of the fluorinated pyrimidine type. We reported the interim reports of this study in colorectal cancer patients at ASCO 2006. Methods: The antitumor effect was the primary endpoint, while the safety, progression-free survival time, and median survival time were the secondary endpoints. The subjects were untreated patients with inoperable advanced colorectal cancer aged 20–75 years. Irinotecan was administered at a dose of 100 mg/m2 (on days 1 and 15) as an intravenous infusion over 90 minutes, and oral S-1 (40 mg/m2) was administered after breakfast and dinner and then withdrawn for 2 weeks. Results: Forty patients were enrolled in the present study. There were 23 men and 17 women. The median age was 62 years (range: 34 to 74 years). Two patients showed grade 4 neutropenia, but the next course could be given safely after dose reduction. Three patients had grade 3 diarrhea, but therapy could be continued with addition of an antidiarrhea drug. No other serious adverse reactions occurred (either hematological or non-hematological), and all patients could receive therapy safely on an outpatient basis. Forty pts. are evaluable for efficacy: RR was 52.5% (CR 1, PR 20, SD 17, PD 2, 95% CI, 37–68%) and Disease Control Rate (CR+PR+SD) was seen in 96.0% of pts. PFS of this regimen is 311 days. MST is not reached. Conclusions: IRIS therapy achieved a high response rate and could be given safely. These findings suggest that the therapy has potential as first-line treatment for inoperable advanced recurrent colorectal cancer. It seems that IRIS is a good treatment equal to FOLFIRI. Non-inferiority randomized phase III trial of IRIS vs. mFOLFOX6 (IFOX study) was planned, and it has been already started now. The latest data will be reported at the meeting. No significant financial relationships to disclose.

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