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]

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.

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.

Safety summary of panitumumab (pmab) in combination with chemotherapy (ctx) from four clinical trials in patients (pts) with metastatic colorectal cancer (mCRC)

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e15005-e15005
Author(s):  
T. J. Price ◽  
M. Peeters ◽  
J. Douillard ◽  
E. Mitchell ◽  
A. Cohn ◽  
...  
Keyword(s):  
Phase Ii ◽  
Safety Data ◽  
Data Monitoring Committee ◽  
Phase Iii ◽  
Phase Ii Trials ◽  
Two Phase ◽  
Phase Ii Studies ◽  
Study Results ◽  
Phase Iii Trials ◽  
Phase Iii Studies

e15005 Background: Pmab is a fully human anti-epidermal growth factor receptor (EGFR) monoclonal antibody approved in the US and EU (wild-type KRAS) as monotherapy for pts with mCRC. Safety data from 4 studies (Siena et al ASCO 2008; Peeters et al ASCO 2008; Cohn et al ASCO 2008; Mitchell et al WORLD GI 2008) of pmab in combination with ctx are summarized. Methods: Two studies are single-arm, phase II trials and two are randomized, phase III trials with pooled, blinded safety data that include ctx-controls. All studies were multicenter. Common pt eligibility criteria included: diagnosis of mCRC with measurable disease per modified RECIST criteria, age ≥ 18 years, and adequate hematologic, renal, hepatic, and metabolic function. All studies required pts to receive FOLFOX, FOLFIRI, or irinotecan ctx in combination with pmab. Pts received pmab 6.0 mg/kg Q2W with FOLFOX Q2W or FOLFIRI Q2W, or pmab 9.0 mg/kg Q3W with irinotecan Q3W. Results from planned interim analyses are available for 3 studies, and results from the final analysis are available for one study. Results: Among the 4-study safety data, 1213 pts received pmab + ctx; 703 pts received pmab + FOLFIRI, 455 pts received pmab + FOLFOX, and 55 pts received pmab + irinotecan. Approximately 1,200 pts were enrolled in each phase III study, and data are available from 1,003 pts who received pmab + ctx and 997 pts who received ctx alone. All pts in the phase III studies, regardless of treatment group, were included in the pooled, blinded interim analysis sets monitored by the data monitoring committee for each study. Safety results for the two phase II studies of pmab + ctx and two phase III studies of pmab ± ctx are summarized (Table). Conclusions: Phase II data are consistent with expectations, and phase III trials are ongoing. A consistent safety profile was observed across studies. [Table: see text] [Table: see text]

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]

Phase III Multicenter Randomized Trial of the Dartmouth Regimen Versus Dacarbazine in Patients With Metastatic Melanoma

1999 ◽  
Vol 17 (9) ◽  
pp. 2745-2745 ◽  
Author(s):  
Paul B. Chapman ◽  
Lawrence H. Einhorn ◽  
Michael L. Meyers ◽  
Scott Saxman ◽  
Alicia N. Destro ◽  
...  
Keyword(s):  
Survival Time ◽  
Tumor Response ◽  
Stage Iv ◽  
Phase Iii ◽  
Phase Ii Trials ◽  
Phase Iii Trial ◽  
Melanoma Patients ◽  
Intent To Treat ◽  
To Receive ◽  
Stage Iv Melanoma

PURPOSE: Several single-institution phase II trials have reported that the Dartmouth regimen (dacarbazine, cisplatin, carmustine, and tamoxifen) can induce major tumor responses in 40% to 50% of stage IV melanoma patients. This study was designed to compare the overall survival time, rate of objective tumor response, and toxicity of the Dartmouth regimen with standard dacarbazine treatment in stage IV melanoma patients. PATIENTS AND METHODS: In this multicenter phase III trial, 240 patients with measurable stage IV melanoma were randomized to receive the Dartmouth regimen (dacarbazine 220 mg/m2 and cisplatin 25 mg/m2 days 1 to 3, carmustine 150 mg/m2 day 1 every other cycle, and tamoxifen 10 mg orally bid) or dacarbazine 1,000 mg/m2. Treatment was repeated every 3 weeks. Patients were observed for tumor response, survival time, and toxicity. RESULTS: Median survival time from randomization was 7 months; 25% of the patients survived ≥ 1 year.There was no difference in survival time between the two treatment arms when analyzed on an intent-to-treat basis or when only the 231 patients who were both eligible and had received treatment were considered. Tumor response was assessable in 226 patients. The response rate to dacarbazine was 10.2% compared with 18.5% for the Dartmouth regimen (P = .09). Bone marrow suppression, nausea/vomiting, and fatigue were significantly more common in the Dartmouth arm. CONCLUSION: There was no difference in survival time and only a small, statistically nonsignificant increase in tumor response for stage IV melanoma patients treated with the Dartmouth regimen compared with dacarbazine. Dacarbazine remains the reference standard treatment for stage IV melanoma.

scholarly journals Unconventional Anticancer Agents: A Systematic Review of Clinical Trials

2006 ◽  
Vol 24 (1) ◽  
pp. 136-140 ◽  
Author(s):  
Andrew J. Vickers ◽  
Joyce Kuo ◽  
Barrie R. Cassileth
Keyword(s):  
Clinical Trials ◽  
Phase I ◽  
Cancer Patients ◽  
Phase Ii ◽  
Dose Finding ◽  
Phase Iii ◽  
High Dose ◽  
Free Text ◽  
Phase Ii Trials ◽  
Off Label

Purpose A substantial number of cancer patients turn to treatments other than those recommended by mainstream oncologists in an effort to sustain tumor remission or halt the spread of cancer. These unconventional approaches include botanicals, high-dose nutritional supplementation, off-label pharmaceuticals, and animal products. The objective of this study was to review systematically the methodologies applied in clinical trials of unconventional treatments specifically for cancer. Methods MEDLINE 1966 to 2005 was searched using approximately 200 different medical subject heading terms (eg, alternative medicine) and free text words (eg, laetrile). We sought prospective clinical trials of unconventional treatments in cancer patients, excluding studies with only symptom control or nonclinical (eg, immune) end points. Trial data were extracted by two reviewers using a standardized protocol. Results We identified 14,735 articles, of which 214, describing 198 different clinical trials, were included. Twenty trials were phase I, three were phase I and II, 70 were phase II, and 105 were phase III. Approximately half of the trials investigated fungal products, 20% investigated other botanicals, 10% investigated vitamins and supplements, and 10% investigated off-label pharmaceuticals. Only eight of the phase I trials were dose-finding trials, and a mere 20% of phase II trials reported a statistical design. Of the 27 different agents tested in phase III, only one agent had a prior dose-finding trial, and only for three agents was the definitive study initiated after the publication of phase II data. Conclusion Unconventional cancer treatments have not been subject to appropriate early-phase trial development. Future research on unconventional therapies should involve dose-finding and phase II studies to determine the suitability of definitive trials.

Design Issues of Randomized Phase II Trials and a Proposal for Phase II Screening Trials

2005 ◽  
Vol 23 (28) ◽  
pp. 7199-7206 ◽  
Author(s):  
Lawrence V. Rubinstein ◽  
Edward L. Korn ◽  
Boris Freidlin ◽  
Sally Hunsberger ◽  
S. Percy Ivy ◽  
...  
Keyword(s):  
Phase Ii ◽  
False Positive ◽  
Standard Treatment ◽  
False Negative ◽  
Error Rates ◽  
Targeted Treatment ◽  
Phase Iii ◽  
Phase Ii Trials ◽  
Treatment Control ◽  
Randomized Phase Ii

Future progress in improving cancer therapy can be expedited by better prioritization of new treatments for phase III evaluation. Historically, phase II trials have been key components in the prioritization process. There has been a long-standing interest in using phase II trials with randomization against a standard-treatment control arm or an additional experimental arm to provide greater assurance than afforded by comparison to historic controls that the new agent or regimen is promising and warrants further evaluation. Relevant trial designs that have been developed and utilized include phase II selection designs, randomized phase II designs that include a reference standard-treatment control arm, and phase II/III designs. We present our own explorations into the possibilities of developing “phase II screening trials,” in which preliminary and nondefinitive randomized comparisons of experimental regimens to standard treatments are made (preferably using an intermediate end point) by carefully adjusting the false-positive error rates (α or type I error) and false-negative error rates (β or type II error), so that the targeted treatment benefit may be appropriate while the sample size remains restricted. If the ability to conduct a definitive phase III trial can be protected, and if investigators feel that by judicious choice of false-positive probability and false-negative probability and magnitude of targeted treatment effect they can appropriately balance the conflicting demands of screening out useless regimens versus reliably detecting useful ones, the phase II screening trial design may be appropriate to apply.

scholarly journals Trends in Phase II Trials for Cancer Therapies

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 178
Author(s):  
Faruque Azam ◽  
Alexei Vazquez
Keyword(s):  
Phase Ii ◽  
Null Model ◽  
Surrogate Endpoint ◽  
Response Rates ◽  
Drug Combinations ◽  
Phase Iii ◽  
Cancer Drug ◽  
Cancer Therapies ◽  
Targeted Agents ◽  
Phase Ii Trials

Background: Drug combinations are the standard of care in cancer treatment. Identifying effective cancer drug combinations has become more challenging because of the increasing number of drugs. However, a substantial number of cancer drugs stumble at Phase III clinical trials despite exhibiting favourable efficacy in the earlier Phase. Methods: We analysed recent Phase II cancer trials comprising 2165 response rates to uncover trends in cancer therapies and used a null model of non-interacting agents to infer synergistic and antagonistic drug combinations. We compared our latest efficacy dataset with a previous dataset to assess the progress of cancer therapy. Results: Targeted therapies reach higher response rates when used in combination with cytotoxic drugs. We identify four synergistic and 10 antagonistic combinations based on the observed and expected response rates. We demonstrate that recent targeted agents have not significantly increased the response rates. Conclusions: We conclude that either we are not making progress or response rate measured by tumour shrinkage is not a reliable surrogate endpoint for the targeted agents.

Biofeedback

2016 ◽  
Vol 4 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Paul Lehrer
Keyword(s):  
Phase Ii ◽  
Real Life ◽  
Phase Iii ◽  
Controlled Trials ◽  
Clinical Environment ◽  
Phase Ii Trials ◽  
Research Support ◽  
Phase Iii Trials ◽  
Psychosomatic Problems ◽  
Biofeedback Research

Although evidence supports the efficacy of biofeedback for treating a number of disorders and for enhancing performance, significant barriers block both needed research and payer support for this method. Biofeedback has demonstrated effects in changing psychophysiological substrates of various emotional, physical, and psychosomatic problems, but payers are reluctant to reimburse for biofeedback services. A considerable amount of biofeedback research is in the form of relatively small well-controlled trials (Phase II trials). This article argues for greater payer support and research support for larger trials in the “real life” clinical environment (Phase III trials) and meta-analytic reviews.

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