The time-to-event continual reassessment method (TITE-CRM) was proposed to handle the problem of long trial duration in Phase 1 trials as a result of late-onset toxicities. Here, we implement the TITE-CRM in dose–finding trials of combinations of agents. When studying multiple agents, monotonicity of the dose-toxicity curve is not clearly defined. Therefore, the toxicity probabilities follow a partial order, meaning that there are pairs of treatments for which the ordering of the toxicity probabilities is not known at the start of the trial. A CRM design for partially ordered trials (PO-CRM) was recently proposed. Simulation studies show that extending the TITE-CRM to the partial order setting produces results similar to those of the PO-CRM in terms of maximum tolerated dose recommendation yet reduces the duration of the trial.
continual reassessment method; dose finding; Phase 1 trials; drug combination; partial order; time-to-event
The aim of a phase I oncology trial is to identify a dose with an acceptable safety profile. Most phase I designs use the dose-limiting toxicity, a binary endpoint, to assess the unacceptable level of toxicity. The dose-limiting toxicity might be incomplete for investigating molecularly targeted therapies as much useful toxicity information is discarded. In this work, we propose a quasi-continuous toxicity score, the total toxicity profile (TTP), to measure quantitatively and comprehensively the overall severity of multiple toxicities. We define the TTP as the Euclidean norm of the weights of toxicities experienced by a patient, where the weights reflect the relative clinical importance of each grade and toxicity type. We propose a dose-finding design, the quasi-likelihood continual reassessment method (CRM), incorporating the TTP score into the CRM, with a logistic model for the dose–toxicity relationship in a frequentist framework. Using simulations, we compared our design with three existing designs for quasi-continuous toxicity score (the Bayesian quasi-CRM with an empiric model and two nonparametric designs), all using the TTP score, under eight different scenarios. All designs using the TTP score to identify the recommended dose had good performance characteristics for most scenarios, with good overdosing control. For a sample size of 36, the percentage of correct selection for the quasi-likelihood CRM ranged from 80% to 90%, with similar results for the quasi-CRM design. These designs with TTP score present an appealing alternative to the conventional dose-finding designs, especially in the context of molecularly targeted agents.
phase I; dose-finding design; continual reassessment method; quasi-continuous endpoint; multiple toxicity score; oncology; molecularly targeted agents; isotonic regression
The continual reassessment method (CRM) is an adaptive model-based design used to estimate the maximum tolerated dose in phase I clinical trials. Asymptotically, the method has been shown to select the correct dose given that certain conditions are satisfied. When sample size is small, specifying a reasonable model is important. While an algorithm has been proposed for the calibration of the initial guesses of the probabilities of toxicity, the calibration of the prior distribution of the parameter for the Bayesian CRM has not been addressed. In this paper, we introduce the concept of least informative prior variance for a normal prior distribution. We also propose two systematic approaches to jointly calibrate the prior variance and the initial guesses of the probability of toxicity at each dose. The proposed calibration approaches are compared with existing approaches in the context of two examples via simulations. The new approaches and the previously proposed methods yield very similar results since the latter used appropriate vague priors. However, the new approaches yield a smaller interval of toxicity probabilities in which a neighboring dose may be selected.
Dose finding; indifference interval; least informative prior; phase I clinical trials
The continual reassessment method (CRM) is an adaptive model-based design used to estimate the maximum tolerated dose in dose finding clinical trials. A way to evaluate the sensitivity of a given CRM model including the functional form of the dose-toxicity curve, the prior distribution on the model parameter, and the initial guesses of toxicity probability at each dose is using indifference intervals. While the indifference interval technique provides a succinct summary of model sensitivity, there are infinitely many possible ways to specify the initial guesses of toxicity probability. In practice, these are generally specified by trial and error through extensive simulations.
By using indifference intervals, the initial guesses used in the CRM can be selected by specifying a range of acceptable toxicity probabilities in addition to the target probability of toxicity. An algorithm is proposed for obtaining the indifference interval that maximizes the average percentage of correct selection across a set of scenarios of true probabilities of toxicity and providing a systematic approach for selecting initial guesses in a much less time consuming manner than the trial and error method. The methods are compared in the context of two real CRM trials.
For both trials, the initial guesses selected by the proposed algorithm had similar operating characteristics as measured by percentage of correct selection, average absolute difference between the true probability of the dose selected and the target probability of toxicity, percentage treated at each dose and overall percentage of toxicity compared to the initial guesses used during the conduct of the trials which were obtained by trial and error through a time consuming calibration process. The average percentage of correct selection for the scenarios considered were 61.5% and 62.0% in the lymphoma trial, and 62.9% and 64.0% in the stroke trial for the trial and error method versus the proposed approach.
We only present detailed results for the empiric dose toxicity curve, although the proposed methods are applicable for other dose toxicity models such as the logistic.
The proposed method provides a fast and systematic approach for selecting initial guesses of probabilities of toxicity used in the CRM that are competitive to those obtained by trial and error through a time consuming process, thus, simplifying the model calibration process for the CRM.
The rate of observed dose-limiting toxicities (DLTs) determines the maximum tolerated dose (MTD) in phase I trials. There are cases in which non-drug-related toxicities or other cause toxicities (OCTs) are flagged as DLTs, or vice versa, due to attribution errors. We aim to assess the impact of such errors on the final estimate of MTD. We compared the impact of attribution errors using two trial designs—the “3+3” dose-escalation scheme and the Continual Reassessment Method (CRM). Two attribution errors are considered: when a DLT is classified as an OCT (Type A error) and when an OCT is misclassified as a DLT (Type B error). The impact of these errors on accuracy, patient safety, sample size, and study duration was evaluated by varying the probability of occurrence of each error through simulated trials. Under no errors, CRM is on average 35% more accurate than 3+3 in finding the true MTD. This improved accuracy is maintained in the presence of errors. At a 15% Type B error rate, CRM recommends a dose within 2 levels of the true MTD 68% of the time, compared to 17% of the time using the 3+3 method. A DLT must be attributed as an OCT 30% of the time in order to increase the accuracy of 3+3, otherwise the method recommends a wrong dose approximately 75% of the time. CRM is more robust to toxicity attribution errors compared to the 3+3 since it uses information from all treated patients, leading to a more accurate MTD estimation at the frequency of attribution errors anticipated in phase I clinical trials.
Toxicity data from cancer trials are summarized into a single outcome, dose-limiting toxicity (DLT), which does not account for multiple lower grade toxic effects nor differentiates between toxicity types and gradations within DLT.
Toxicity data were summarized into a toxicity burden score (TBS) using a weighted sum. The severity weights were estimated via regression using historical data. We demonstrated the method using historical data from a bortezomib trial and illustrated the advantages of defining DLT based on TBS in a simulated dose-finding trial.
The estimated weights were 0.17, 0.40 and 0.85 for grade 1/2, grade 3 and grade 4 platelets, respectively; 0.19, 0.64, 1.03 and 2.53 for grade 1, 2, 3 and 4 neuropathy, respectively and 0.17 for each grade 3 or higher nonhematologic toxic effects unrelated to treatment. In the simulated trial, the probability of selecting doses above the maximum tolerated dose decreased when using the DLT defined based on TBS.
TBS is a feasible approach to summarize toxicity. It includes information from the grades and types of multiple toxic effects and can be applied in all phases of drug development. Further efforts should focus on validating the method in a large prospective study before applying it in practice.
adverse event summary; dose-limiting toxicity; toxicity; toxicity types and grades
The Traditional Method (TM), also known as the 3+3 up-and-down design, and the Continual Reassessment Method (CRM) are commonly used in Phase I Oncology Trials to identify the maximum tolerated dose (MTD). The Rolling-6 is a relative newcomer which was developed to shorten trial duration by minimizing the period of time during which the trial is closed to accrual for toxicity assessment. In this manuscript we have compared the performance of these three approaches via simulations not only with respect to the usual parameters such as overall toxicity, sample size and percentage of patients treated at doses above the MTD but also in terms of trial duration and the dose chosen as the MTD. Our results indicate that the toxicity rates are comparable across the three designs, but the TM and the Rolling-6 tend to treat a higher percentage of patients at doses below the MTD. With respect to trial duration, Rolling-6 leads to shorter trials compared to the TM but not compared to the CRM. Additionally, the doses identified as the MTD by the TM and the Rolling-6 differ in a large percentage of trials. Our results also indicate that the body surface area-based dosing used in pediatric trials can make a difference in dose escalation/de-escalation patterns in the CRM compared to the cases where such variations are not taken into account in the calculations, even leading to different MTDs in some cases.
Body Surface Area Based Dosing; Pediatric Trials; Dose Finding; Maximum Tolerated Dose
Isotonic Design using Normalized Equivalent Toxicity Score (ID-NETS) is a novel Phase I design that integrates the novel toxicity scoring system originally proposed by Chen et al.  and the original Isotonic Design proposed by Leung et al. . ID-NETS has substantially improved the accuracy of maximum tolerated dose (MTD) estimation and trial efficiency in the Phase I clinical trial setting by fully utilizing all toxicities experienced by each patient and treating toxicity response as a quasi-continuous variable instead of a binary indicator of dose limiting toxicity (DLT). To facilitate the incorporation of the ID-NETS method into the design and conduct of Phase I clinical trials, we have designed and developed a user-friendly software, ID-NETS©TM, which has two functions: 1) Calculating the recommended dose for the subsequent patient cohort using available completed data; and 2) Performing simulations to obtain the operating characteristics of a trial designed with ID-NETS. Currently, ID-NETS©TMv1.0 is available for free download at http://winshipbbisr.emory.edu/IDNETS.html.
Isotonic design; normalized equivalent toxicity score; maximum tolerated dose; dose limiting toxicity; cancer phase I clinical trial; software.
Late-onset (LO) toxicities are a serious concern in many phase I trials. Since most dose-limiting toxicities occur soon after therapy begins, most dose-finding methods use a binary indicator of toxicity occurring within a short initial time period. If an agent causes LO toxicities, however, an undesirably large number of patients may be treated at toxic doses before any toxicities are observed. A method addressing this problem is the time-to-event continual reassessment method (TITE-CRM, Cheung and Chappell, 2000). We propose a Bayesian dose-finding method similar to the TITE-CRM in which doses are chosen using time-to-toxicity data. The new aspect of our method is a set of rules, based on predictive probabilities, that temporarily suspend accrual if the risk of toxicity at prospective doses for future patients is unacceptably high. If additional follow-up data reduce the predicted risk of toxicity to an acceptable level, then accrual is restarted, and this process may be repeated several times during the trial. A simulation study shows that the proposed method provides a greater degree of safety than the TITE-CRM, while still reliably choosing the preferred dose. This advantage increases with accrual rate, but the price of this additional safety is that the trial takes longer to complete on average.
Adaptive design; Bayesian inference; Dose finding; Isotonic regression; Latent variables; Markov chain Monte Carlo; Ordinal modeling; Predictive probability
Patients recruited in phase I oncology trials are often treated at doses lower than the maximum tolerated dose (MTD), and therefore may not receive the most efficacious dose available, despite their expectations to the contrary. This report investigates the consequences of allowing a patient choice of dose within a common dose-escalation scheme.
Trials using the continual reassessment method of dose escalation are simulated, with a modification of the rules to allow patients to choose a higher dose if they wish. The effect of allowing this choice is assessed in terms of probability of toxicity and probability of being treated at the MTD or higher.
The simulations show that allowing a patient choice of dose reduces the proportions of patients treated at doses lower than the MTD, and has little impact on the overall probability of correct identification of the MTD.
The results illustrate the principle that a choice of dose can be offered to patients in such trials without compromising the overall properties of the study.
phase I; oncology; continual reassessment method; ethics; dose escalation
In dose-finding clinical study, it is common that multiple endpoints are of interest. For instance, efficacy and toxicity endpoints are both primary in clinical trials. In this article, we propose a joint model for correlated efficacy-toxicity outcome constructed with Archimedean Copula, and extend the continual reassessment method (CRM) to a bivariate trial design in which the optimal dose for phase III is based on both efficacy and toxicity. Specially, considering numerous cases that continuous and discrete outcomes are observed in drug study, we will extend our joint model to mixed correlated outcomes. We demonstrate through simulations that our algorithm based on Archimedean Copula model has excellent operating characteristics.
Toxicity grades underlie the definition of a dose limiting toxicity (DLT) but in the majority of phase I designs, the information contained in the individual grades is not used. Some authors have argued that it may be more appropriate to consider a polytomous rather than dichotomous response.
We investigate whether the added information on individual grades can improve the operating characteristics of the Continual Reassessment Method (CRM).
We compare the original CRM design for a binary response with two stage CRM designs which make di erent use of lower-grade toxicity information via simulations. Specifically we study; a two-stage design that utilizes lower-grade toxicities in the first stage only, during the initial non model-based escalation, and two-stage designs where lower grades are used throughout the trial via explicit models. We postulate a model relating the rates of lower grade toxicities to the rate of DLTs, or assume the relative rates of low to high grade toxicities is unknown. The designs were compared in terms of accuracy, patient allocation and precision.
Significant gains can be achieved when using grades in the first stage of a two-stage design. Otherwise, only modest improvements are seen when the information on grades is exploited via the use of explicit models, where the parameters are known precisely. CRM with some use of grade information, increases the number of patients treated at the MTD by approximately 5%. The additional information from lower grades can lead to a small increase in the precision of our estimate of the MTD.
Our comparisons are not exhaustive and it would be worth studying other models and situations.
Although, the gains in performance were not as great as we had hoped, we observed no cases where the performance of CRM was poorer. Our recommendation is that investigators might consider using graded toxicities at the design stage.
Dose-finding; Phase I; Toxicity Grades; Dose Limiting Toxicity
The continual reassessment method (CRM) is a commonly used dose-finding design for phase I clinical trials. Practical applications of this method have been restricted by two limitations: (1) the requirement that the toxicity outcome needs to be observed shortly after the initiation of the treatment; and (2) the potential sensitivity to the prespecified toxicity probability at each dose. To overcome these limitations, we naturally treat the unobserved toxicity outcomes as missing data, and use the expectation-maximization (EM) algorithm to estimate the dose toxicity probabilities based on the incomplete data to direct dose assignment. To enhance the robustness of the design, we propose prespecifying multiple sets of toxicity probabilities, each set corresponding to an individual CRM model. We carry out these multiple CRMs in parallel, across which model selection and model averaging procedures are used to make more robust inference. We evaluate the operating characteristics of the proposed robust EM-CRM designs through simulation studies and show that the proposed methods satisfactorily resolve both limitations of the CRM. Besides improving the MTD selection percentage, the new designs dramatically shorten the duration of the trial, and are robust to the prespecification of the toxicity probabilities.
Adaptive design; Expectation-maximization algorithm; Late-onset toxicity; Maximum tolerated dose; Missing data; Model averaging; Model selection
Epidemiologic data support an inverse association between green tea intake and breast cancer risk and numerous experimental studies have demonstrated the anti-tumor effects of its main component, epigallocatechin gallate (EGCG). We conducted a phase IB dose escalation trial in women with a history of stage I-III hormone receptor-negative breast cancer of an oral green tea extract, Polyphenon E (Poly E) 400mg, 600mg, 800mg bid or matching placebo for 6 months. The primary endpoint was to determine the maximum tolerated dose (MTD), defined as the dose that causes 25% dose limiting toxicity (DLT, grade≥2). Assignment to dose level was based upon an adaptive design, the continual reassessment method. A mammogram and random core biopsy of the contralateral breast were obtained at baseline and 6 months and serial blood/urine collections every 2 months for biomarker analyses. Forty women were randomized: 10 to placebo, 30 to Poly E (16 at 400mg, 11 at 600mg, 3 at 800mg). There was 1 DLT at 400mg (grade 3 rectal bleeding), 3 DLTs at 600mg (grade 2 weight gain, grade 3 indigestion and insomnia), and 1 DLT at 800mg (grade 3 liver function abnormality). The DLT rate at 600mg was 27% (3/11). Pharmacologic levels of total urinary tea polyphenols were achieved with all three dose levels of Poly E. Using a novel phase I trial design, we determined the MTD for Poly E to be 600mg bid. This study highlights the importance of assessing toxicity for any chemopreventive agent being developed for chronic use in healthy individuals.
green tea; chemoprevention; breast cancer; biomarkers
The goal of phase I cancer trials is to determine the highest dose of a treatment regimen with an acceptable toxicity rate. Traditional designs for phase I trials, such as the Continual Reassessment Method (CRM) and the 3+3 design, require each patient or a cohort of patients to be fully evaluated for the dose-limiting toxicity (DLT) before new patients can be enrolled. As such, the trial duration may be prohibitively long. The Time-to-Event Continual Reassessment Method (TITE-CRM, Cheung and Chappell, 2000) circumvents this limitation by allowing staggered patient accrual without the need for complete DLT follow-up of previously treated patients. However, in the setting of fast patient accrual and late-onset toxicities, the TITE-CRM results in overly aggressive dose escalation and exposes a considerable number of patients to toxic doses. We examine a modification to the TITE-CRM proposed by the original TITE-CRM creator and propose an alternative approach useful in this setting by incorporating an accrual suspension rule. A simulation study designed based on a neuro-oncology trial indicates that the modified methods provide a much improved degree of safety than the TITE-CRM while maintaining desirable design accuracy. The practical aspects of the proposed designs are discussed. The modifications presented are useful when planning phase I trials involving chemoradiation therapy.
phase I clinical trials; time-to-event continual reassessment method; dose finding; late-onset toxicity; adaptive design; Bayesian inference
A phase I trial of lenalidomide was performed in children with recurrent, refractory, or progressive primary CNS tumors to estimate the maximum-tolerated dose (MTD) and to describe the toxicity profile and pharmacokinetics.
Patients and Methods
Lenalidomide was administered by mouth daily for 21 days, repeated every 28 days. The starting dose was 15 mg/m2/d orally, and the dose was escalated according to a modified continuous reassessment method. Correlative studies included pharmacokinetics obtained from consenting patients on course 1, day 1, and at steady-state (between days 7 and 21).
Fifty-one patients (median age, 10 years; range, 2 to 21 years) were enrolled. Forty-four patients were evaluable for dose finding, and 49 patients were evaluable for toxicity. The primary toxicity was myelosuppression, but the MTD was not defined because doses up to 116 mg/m2/d were well-tolerated during the dose-finding period. Two objective responses were observed (one in thalamic juvenile pilocytic astrocytoma and one in optic pathway glioma) at dose levels of 88 and 116 mg/m2/d. Twenty-three patients, representing all dose levels, received ≥ six cycles of therapy. Pharmacokinetic analysis demonstrated that the lenalidomide area under the concentration-time curve from 0 to 24 hours and maximum plasma concentration increased with dosage over the range studied.
Lenalidomide was tolerable in children with CNS tumors at doses of 116 mg/m2/d during the initial dose-finding period. The primary toxicity is myelosuppression. Antitumor activity, defined by both objective responses and long-term stable disease, was observed, primarily in patients with low-grade gliomas.
The trend of treating patients with combined drugs has grown in cancer clinical trials. Often, evaluating the synergism of multiple drugs is the primary motivation for such drug-combination studies. To enhance the patient response, a new cancer therapeutic agent is often investigated together with an existing standard of care (SOC) agent. At least a certain amount of dosage of the SOC is administered in order to maintain some therapeutic effects in patients. For clinical trials involving a continuous-dose SOC and a discrete-dose agent, we propose a two-stage Bayesian adaptive dose-finding design. The first stage takes a continual reassessment method to locate the appropriate dose for the discrete-dose agent while fixing the continuous-dose SOC at the minimal therapeutic dose. In the second stage, we make a fine dose adjustment by calibrating the continuous dose to achieve the target toxicity rate as closely as possible. Dose escalation or de-escalation is based on the posterior estimates of the joint toxicity probabilities of combined doses. As the toxicity data accumulate during the trial, we adaptively assign each cohort of patients to the most appropriate dose combination. We conduct extensive simulation studies to examine the operating characteristics of the proposed two-stage design and demonstrate the design's good performance with practical scenarios.
Bayesian adaptive design; Combined drugs; Continual reassessment method; Maximum tolerated dose; Phase I trial; Toxicity probability; Two-stage design
Currently many dose finding clinical trial designs, including the continual reassessment method (CRM) and the standard ‘3+3’ design, dichotomize toxicity outcomes based on pre-specified dose-limiting toxicity criteria. This loss of information is particularly inefficient due to the small sample sizes in phase I trials. Common Toxicity Criteria (CTCAEv3.0) classify adverse events into grades 1 through 5, which range from 1 as a mild adverse event to 5 as death related to an adverse event. In this paper, we extend the CRM to include ordinal toxicity outcomes as specified by CTCAEv3.0 using the proportional odds model and compare results with the dichotomous CRM. A sensitivity analysis of the new design compares various target dose-limiting toxicity rates, sample sizes, and cohort sizes. This design is also assessed under various dose-toxicity relationship models including proportional odds models as well as those that violate the proportional odds assumption. A simulation study shows that the proportional odds CRM performs as well as the dichotomous CRM on all criteria compared (including safety criteria such as percentage of patients treated at highly toxic or suboptimal dose levels) and with improved estimation of the MTD when the PO assumption is not violated. These findings suggest that it is beneficial to incorporate ordinal toxicity endpoints into phase I trial designs.
continual reassessment method; dose finding; ordinal; proportional odds
To evaluate the toxicity, pharmacological, and biological properties of the combination of bortezomib, etoposide, and carboplatin in adults with advanced solid malignancies.
Patients and methods
Patients received escalating doses of bortezomib, etoposide, and carboplatin every 21 days. Surrogate markers of angiogenesis were evaluated.
Twenty-four patients received 64 courses of therapy. The most common treatment-related adverse events were myelosuppression. Dose-limiting grade 3 and 4 neutropenia and thrombocytopenia were observed when bortezomib was given on days 1, 4, 8, 11. With revised dosing, the maximum tolerated dose (MTD) of bortezomib 0.75 mg/m2 (days 1, 8), etoposide 75 mg/m2 (days 1–3), and carboplatin AUC 5 (day 1) was well tolerated, and are the recommended doses for further studies with this combination. No objective responses were observed, however stable disease was noted for greater or equal to four cycles in nine highly refractory patients.
Bortezomib; Combination chemotherapy; Phase I clinical trial; Proteasome inhibitor
In this article we provide additional support for the use of a model based design in pediatric Phase I trials, and present our modifications to the continual reassessment method (CRM), which were largely motivated by specific challenges we encountered in the context of the Pediatric Brain Tumor Consortium trials. We also summarize the results of our extensive simulations studying the operating characteristics of our modified approach and contrasting it to the empirically based traditional method (TM). Compared to the TM, our simulations indicate that the modified version of CRM is more accurate; exposes fewer patients to potentially toxic doses; and tends to require fewer patients. Further, the CRM based MTD has a consistent definition across trials, which is important, especially in a consortium setting where multiple agents are being tested in studies that are often running simultaneously and accruing from the same patient population.
Continual Reassessment Method; Up-and-down studies; Dose-toxicity model; simulation; dose finding
Karenitecin is a highly lipophilic camptothecin analogue with a lactone ring that is relatively resistant to inactivating hydrolysis under physiologic conditions. This phase I clinical trial was conducted to determine the maximum tolerated dose (MTD) of karenitecin in adults with recurrent malignant glioma (MG), to describe the effects of enzyme-inducing antiseizure drugs (EIASDs) on its pharmacokinetics, and to obtain preliminary evidence of activity. Karenitecin was administered intravenously over 60 min daily for 5 consecutive days every 3 weeks to adults with recurrent MG who had no more than one prior chemotherapy regimen. The continual reassessment method was used to escalate doses, beginning at 1.0 mg/m2/day, in patients stratified by EIASD use. Treatment was continued until disease progression or treatment-related dose-limiting toxicity (DLT). Plasma pharmacokinetics was determined for the first daily dose of karenitecin. Thirty-two patients (median age, 52 years; median KPS score, 90) were accrued. Seventy-eight percent had glioblastoma, and 22% had anaplastic glioma. DLT was reversible neutropenia or thrombocytopenia. The MTD was 2.0 mg/m2 in +EIASD patients and 1.5 mg/m2 in −EIASD patients. The mean (±SD) total body clearance of karenitecin was 15.9 ± 9.6 liters/h/m2 in +EIASD patients and 10.2 ± 3.5 liters/h/m2 in −EIASD patients (p = 0.02). No objective responses were observed in 11 patients treated at or above the MTD. The total body clearance of karenitecin is significantly enhanced by the concurrent administration of EIASDs. This schedule of karenitecin, a novel lipophilic camptothecin analogue, has little activity in recurrent MG.
brain cancer; cancer therapy; drug interactions; glioblastoma multiforme; karenitecin
Bortezomib targets molecular dysregulation of nuclear factor-κB activation and cell cycle control, which are characteristic features of diffuse large B-cell lymphoma (DLBCL). We evaluated the safety and efficacy of bortezomib treatment with dose-dense cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) every 2 weeks (CHOP-14).
Untreated DLBCL patients were enrolled. A phase I dose-escalation study with 1.0, 1.3, and 1.6 mg/m2 bortezomib administration on day 1 and 4 in addition to the CHOP-14 regimen was performed to determine the maximum tolerated dose (MTD) and the dose-limiting toxicity (DLT). Lenograstim 5 µg/kg/d was administered on day 4-13. The bortezomib dose from the phase I study was used in the phase II study.
Nine and 37 patients were enrolled in the phase I and phase II studies, respectively. The analysis of the phase II results (40 patients) included data of the 3 patients in the last MTD dose cohort of the phase I trial. During the phase I trial, no DLT was observed at any bortezomib dose; therefore, the recommended dose was 1.6 mg/m2. In phase II, the overall response rate was 95% (complete response: 80%; partial response: 15%). Nine out of the 40 patients showed grade 3 sensory neuropathy, and 22 required at least 1 dose reduction. Three patients could not complete the intended 6 cycles of treatment because of severe neuropathy.
Bortezomib plus CHOP-14 was highly effective for the treatment of untreated DLBCL patients, but in many cases, dose or schedule modification was required to reduce neurotoxicity.
Bortezomib; CHOP-14; Diffuse large B-cell lymphoma
Most of the current designs used for Phase I dose finding trials in oncology will either involve only a single cytotoxic agent or will impose some implicit ordering among the doses. The goal of the studies is to estimate the maximum tolerated dose (MTD), the highest dose that can be administered with an acceptable level of toxicity. A key working assumption of these methods is the monotonicity of the dose–toxicity curve.
Here we consider situations in which the monotonicity assumption may fail. These studies are becoming increasingly common in practice, most notably, in phase I trials that involve combinations of agents. Our focus is on studies where there exist pairs of treatment combinations for which the ordering of the probabilities of a dose-limiting toxicity cannot be known a priori.
We describe a new dose-finding design which can be used for multiple-drug trials and can be applied to this kind of problem. Our methods proceed by laying out all possible orderings of toxicity probabilities that are consistent with the known orderings among treatment combinations and allowing the continual reassessment method (CRM) to provide efficient estimates of the MTD within these orders. The design can be seen to simplify to the CRM when the full ordering is known.
We study the properties of the design via simulations that provide comparisons to the Bayesian approach to partial orders (POCRM) of Wages, Conaway, and O'Quigley. The POCRM was shown to perform well when compared to other suggested methods for partial orders. Therefore, we comapre our approach to it in order to assess the performance of the new design.
A limitation concerns the number of possible orders. There are dose-finding studies with combinations of agents that can lead to a large number of possible orders. In this case, it may not be feasible to work with all possible orders.
The proposed design demonstrates the ability to effectively estimate MTD combinations in partially ordered dosefinding studies. Because it relaxes the monotonicity assumption, it can be considered a multivariate generalization of the CRM. Hence, it can serve as a link between single and multiple-agent dosefinding trials.
This multi-institutional phase I trial was designed to determine the maximum tolerated dose (MTD) of cilengitide (EMD 121974) and evaluate the use of perfusion MRI in patients with recurrent malignant glioma.
Patients and Methods
Patients received cilengitide twice weekly on a continuous basis. A treatment cycle was defined as 4 weeks. Treatment related dose limiting toxicity was defined as any grade 3 or 4 non-hematological toxicity or grade 4 hematological toxicity of any duration.
A total of 51 patients were enrolled in cohorts of 6 patients to doses of 120, 240, 360, 480, 600, 1200, 1800, and 2400 mg/m2 administered as a twice weekly intravenous infusion. Three patients progressed early and were inevaluable for toxicity assessment. The dose limiting toxicities observed were: one thrombosis (120 mg/m2), one grade 4 joint and bone pain (480 mg/m2), one thrombocytopenia (600 mg/m2) and one anorexia, hypoglycemia, hyponatremia (800 mg/m2). The MTD was not reached. Two patients demonstrated complete response, three patients had partial response, and four patients had stable disease. Perfusion MRI revealed a significant relationship between the change in tumor relative cerebral blood flow (rCBF) from baseline and area under the plasma concentration versus time curve after 16 weeks of therapy.
1) Cilengitide is well tolerated to doses of 2400 mg/m2; 2) Durable complete and partial responses were seen in this phase I study; 3) Clinical response appears related to rCBF changes.
COX-2 inhibitors, such as celecoxib, and ubiquitin-proteasome pathway inhibitors, such as bortezomib, can down-regulate NF-κB, a transcription factor implicated in tumor growth. The objective of this study was to determine the maximum tolerated dose and dose-limiting toxicities of bortezomib in combination with celecoxib in patients with advanced solid tumors.
Patients received escalating doses of bortezomib either on a weekly schedule (days 1, 8, 15, 22, and 29 repeated every 42 days) or on a twice-weekly administration schedule (days 1, 4, 8, and 11 repeated every 21 days), in combination with escalating doses of celecoxib twice daily throughout the study period from 200 mg to 400 mg twice daily.
No dose-limiting toxicity was observed during the study period. Two patients had stable disease lasting for four and five months each, and sixteen patients developed progressive disease.
The combination of bortezomib and celecoxib was well tolerated, without dose limiting toxicities observed throughout the dosing ranges tested, and will be studied further at the highest dose levels investigated.
Trial registration number