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

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.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e19049-e19049 ◽  
Author(s):  
Laurent Claret ◽  
Pierre Mancini ◽  
Bernard Sebastien ◽  
Christine Veyrat-Follet ◽  
Rene Bruno

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]


2009 ◽  
Vol 27 (25) ◽  
pp. 4103-4108 ◽  
Author(s):  
Laurent Claret ◽  
Pascal Girard ◽  
Paulo M. Hoff ◽  
Eric Van Cutsem ◽  
Klaas P. Zuideveld ◽  
...  

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.


2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e15005-e15005
Author(s):  
T. J. Price ◽  
M. Peeters ◽  
J. Douillard ◽  
E. Mitchell ◽  
A. Cohn ◽  
...  

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]


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4040-4040
Author(s):  
David Cucchi ◽  
Tobias Polak ◽  
Gert J. Ossenkoppele ◽  
Jacob M. Rowe ◽  
Elihu H. Estey

Abstract Reports of "positive" results in early phase trials as presented at ASH presumably herald therapeutic advances, or at a minimum, a larger, potentially confirmatory, randomized trial. However, the predictive value of an ASH abstract reporting positive results in AML for subsequent clinical utility seems low (Estey 2006, ASH). Furthermore, not all results presented at ASH are published in peer-reviewed journals, and selectively publishing positive results leads to publication bias. Moreover, truly negative studies may be scientifically more rigorous and accurate than positive studies given the unequivocal findings. The extent of publication bias is unknown as is the frequency with which positive or negative abstracts lead to subsequent investigation in phase III and the reasons why positive phase II studies might not progress to phase III. We downloaded all 2013 - 2015 ASH abstracts (N = 17,251) and evaluated all abstracts reporting phase II clinical trials (N = 371) of novel drugs and therapeutic regimens presented at ASH in these years, covering investigational treatments of MM, CLL, AML, DLBCL, MDS, NHL, ALL, CML, MCL, SLL, other lymphomas and POEMS. We first scored abstracts "positive", "negative" or "inconclusive". Criteria for a positive abstract were words/phrases such as "encouraging", "promising", "could represent a novel therapeutic option" and "warrants investigation in a randomized trial". Negative abstracts included terms such as "does not support further research" and "demonstrates no clinical activity". The remainder were scored as inconclusive. Using this approach, we scored 296/371 (80%) abstracts as positive, 37/371 (10%) as negative, and 38/371 (10%) as inconclusive. 292/371 abstracts (79%) were published in peer-reviewed journals. The abstract conclusion (positive, negative or inconclusive) was not associated with publication in a peer-reviewed journal. Most frequently, studies were published in Blood (34/292 [11.6%]) and British Journal of Haematology (39/292 [13.4%]) . In Blood, 91% (31/34) of the studies were positive. British Journal of Haematology published significantly more negative studies than Blood (26%, Fisher Exact p = 0.02). Abstracts reporting studies with larger sample sizes tended to be published more often (p = 0.066). Differences exist between the abstract conclusion and later peer-reviewed publications. Of positive ASH abstracts, 6% changed to a negative conclusion in the peer-reviewed publication. Similarly, 6.5% of the initial negative abstract later reversed to a positive conclusion. 53% of positive abstracts did not lead to phase III studies, as registered on clinicaltrials.gov. Subsequently, regimens described in positive peer-reviewed publications did not proceed to phase III research in 48%. To explore why, we sent questionnaires to the first and/or last authors of positive studies not prompting phase III trials. 52% responded. Failure of positive phase II trials to proceed to phase III was due to the decision by the pharmaceutical company to halt clinical investigation (44%), lack of any intent to study the drug in phase III in the first place (40%), insufficient funding (35%), insufficient efficacy (despite the "positive" abstract; 33%) and safety concerns (4%) (Figure). Additional reasons for not proceeding to phase III were the availability of newer regimens, the rarity of the disease, or when regulatory approval had already been obtained after phase II. In conclusion, "positive" and "negative" ASH abstracts are published as full papers equally often, although the positive ones may be published more often in journals with higher "impact factors". More than half of the regimens presented in positive ASH abstracts remain unevaluated in randomized phase III trials. A separate problem is the likely tendency to disproportionately submit (and/or accept) positive, rather than negative, studies to ASH in the first place. We believe our findings raise issues in clinical research that may not be in the best interest of patients. This demands more consideration than it currently receives. Figure 1 Figure 1. Disclosures Ossenkoppele: Astellas: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Abbvie, AGIOS, BMS/Celgene Astellas,AMGEN, Gilead,Servier,JAZZ,Servier Novartis: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Gilead: Consultancy, Honoraria. Rowe: Biosight Inc.: Consultancy.


2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6604-6604
Author(s):  
S. M. Ueda ◽  
V. E. Sugiyama ◽  
C. Stave ◽  
J. Y. Shin ◽  
B. J. Monk ◽  
...  

6604 Background: To identify the characteristics of a phase II study that predict for a subsequent positive phase III trial. Methods: All phase II studies and subsequent phase III clinical trials on biologics in advanced cancers published from 1985 to 2005 were extracted. Chi-square test and logistic regression models were used for analyses. Results: 383 phase III clinical trials and their preceding phase II studies were identified. 183 (47.8%) phase III trials were “positive” and 200 (52.2%) were negative. 220 trials (57.4%) used biologics alone and 162 (42.3%) used a combination of biologics and chemotherapy. Over the study periods 1985–1990, 1991–1995, 1996–2000, 2001–2005, the percentage of phase II studies that led to positive phase III trials increased from 37.7% to 33.3% to 56.0% to 76.8% (p<0.001). The interval between the publication of phase II and III studies, 0.5–5, 6–10, 11–15, and 16–20 years were also associated with the success of phase III trial, 55.6%, 42.2%, 32.6%, and 10.0%, respectively (p<0.001). Phase II studies from multiple rather than single institutions were more likely to have a successful trial (60.4% vs. 39.4%; p<0.001). The percent of successful trials from pharmaceutical companies was significantly higher compared to academic, cooperative groups, and research institutes (89.5% vs. 44.2%, 45.2%, 46.3%; p=0.002). The publication of the phase II studies in journals with an impact factor of 8 or greater compared to those less than 8 was also predictive (44.1% vs. 58.0%; p=0.024). Phase II studies with a lower attrition rate were also associated with a positive phase III trial (61.1% vs. 41.8%; p=0.025). On multivariable analysis, all factors, except for journal impact factor, were independent predictive factors for a positive phase III trial. Conclusions: In phase II biologic studies, characteristics such as larger number of patients, more recent year of study, multiple vs. single institution participation, shorter time period between publication of phase II to phase III trial, and lower rate of attrition were predictive factors of success in a phase III trial. Investigators need to be cognizant of these phase II study characteristics before designing phase III trials. No significant financial relationships to disclose.


2017 ◽  
Vol 14 (3) ◽  
pp. 277-285 ◽  
Author(s):  
Simon Wandel ◽  
Beat Neuenschwander ◽  
Christian Röver ◽  
Tim Friede

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.


Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 178
Author(s):  
Faruque Azam ◽  
Alexei Vazquez

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.


1988 ◽  
Vol 6 (2) ◽  
pp. 308-314 ◽  
Author(s):  
M E Horowitz ◽  
E Etcubanas ◽  
M L Christensen ◽  
J A Houghton ◽  
S L George ◽  
...  

We describe events that led to successful testing of melphalan, one of the nitrogen mustard compounds, in children with newly diagnosed, poor-risk rhabdomyosarcoma (RMS). Preclinical studies with xenografts of human RMS, growing in the flanks of immune-deprived mice, had indicated superior oncolytic activity by melphalan compared with other agents commonly used to treat this tumor. However, in a conventional phase II trial, melphalan failed to produce partial responses in 12 of 13 heavily pretreated patients with recurrent tumors. Subsequent comparison of the drug's pharmacokinetics in mice and patients indicated that its poor clinical performance was not the result of interspecies differences in drug disposition. Therefore, we elected to retest melphalan in untreated patients, before they were enrolled in a phase III study. Of 13 children who received the drug for 6 weeks, ten had partial responses, confirming the significant antitumor activity seen in the xenograft system. These findings illustrate the inherent limitations of phase II drug trials in previously treated patients and suggest a useful paradigm for the development of antineoplastic drugs.


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