Antagonizing CD105 and androgen receptor to target stromal-epithelial interactions for clinical benefit.

Androgen receptor signaling inhibitors (ARSIs) are standard of care for advanced prostate cancer (PCa) patients. Eventual resistance to ARSIs can include the expression of androgen receptor (AR) splice variant, AR-V7, expression as a recognized means of ligand-independent androgen signaling. We demonstrated that interleukin (IL)-6-mediated AR-V7 expression requires bone morphogenic protein (BMP) and CD105 receptor activity in both PCa and associated fibroblasts. Chromatin immunoprecipitation supported CD105-dependent ID1- and E2F-mediated expression of RBM38. Further, RNA immune precipitation demonstrated RBM38 binds the AR-cryptic exon 3 to enable AR-V7 generation. The forced expression of AR-V7 by primary prostatic fibroblasts diminished PCa sensitivity to ARSI. Conversely, downregulation of AR-V7 expression in cancer epithelia and associated fibroblasts was achieved by a CD105-neutralizing antibody, carotuximab. These compelling pre-clinical findings initiated an interventional study in PCa patients developing ARSI resistance. The combination of carotuximab and ARSI (i.e., enzalutamide or abiraterone) provided disease stabilization in four of nine assessable ARSI-refractory patients. Circulating tumor cell evaluation showed AR-V7 downregulation in the responsive subjects on combination treatment and revealed a three-gene panel that was predictive of response. The systemic antagonism of BMP/CD105 signaling can support ARSI re-sensitization in pre-clinical models and subjects that have otherwise developed resistance due to AR-V7 expression.

Simulation study comparing analytical methods for single-item longitudinal patient-reported outcomes data.

PURPOSE: Efficient analytical methods are necessary to make reproducible inferences on single-item longitudinal ordinal patient-reported outcome (PRO) data. A thorough simulation study was performed to compare the performance of the semiparametric probabilistic index models (PIM) with a longitudinal analysis using parametric cumulative logit mixed models (CLMM). METHODS: In the setting of a control and intervention arm, we compared the power of the PIM and CLMM to detect differences in PRO adverse event (AE) between these groups using several existing and novel summary scores of PROs. For each scenario, PRO data were simulated using copula multinomial models. Comparisons were also exemplified using clinical trial data. RESULTS: On average, CLMM provided substantially greater power than the PIM to detect differences in PRO-AEs between the groups when the baseline-adjusted method was used, and a small advantage in power when using the baseline symptom as a covariate. CONCLUSION: Although the CLMM showed the best performance among analytical methods, it relies on assumptions difficult to verify and that might not be fulfilled in the real world, therefore our recommendation is the use of PIM models with baseline symptom as a covariate.

Cancer epithelia-derived mitochondrial DNA is a targetable initiator of a paracrine signaling loop that confers taxane resistance.

Stromal-epithelial interactions dictate cancer progression and therapeutic response. Prostate cancer (PCa) cells were identified to secrete greater concentration of mitochondrial DNA (mtDNA) compared to noncancer epithelia. Based on the recognized coevolution of cancer-associated fibroblasts (CAF) with tumor progression, we tested the role of cancer-derived mtDNA in a mechanism of paracrine signaling. We found that prostatic CAF expressed DEC205, which was not expressed by normal tissue-associated fibroblasts. DEC205 is a transmembrane protein that bound mtDNA and contributed to pattern recognition by Toll-like receptor 9 (TLR9). Complement C3 was the dominant gene targeted by TLR9-induced NF-κB signaling in CAF. The subsequent maturation complement C3 maturation to anaphylatoxin C3a was dependent on PCa epithelial inhibition of catalase in CAF. In a syngeneic tissue recombination model of PCa and associated fibroblast, the antagonism of the C3a receptor and the fibroblastic knockout of TLR9 similarly resulted in immune suppression with a significant reduction in tumor progression, compared to saline-treated tumors associated with wild-type prostatic fibroblasts. Interestingly, docetaxel, a common therapy for advanced PCa, further promoted mtDNA secretion in cultured epithelia, mice, and PCa patients. The antiapoptotic signaling downstream of anaphylatoxin C3a signaling in tumor cells contributed to docetaxel resistance. The inhibition of C3a receptor sensitized PCa epithelia to docetaxel in a synergistic manner. Tumor models of human PCa epithelia with CAF expanded similarly in mice in the presence or absence of docetaxel. The combination therapy of docetaxel and C3 receptor antagonist disrupted the mtDNA/C3a paracrine loop and restored docetaxel sensitivity.

A nonparametric Bayesian method for dose finding in drug combinations cancer trials.

We propose an adaptive design for early-phase drug-combination cancer trials with the goal of estimating the maximum tolerated dose (MTD). A nonparametric Bayesian model, using beta priors truncated to the set of partially ordered dose combinations, is used to describe the probability of dose limiting toxicity (DLT). Dose allocation between successive cohorts of patients is estimated using a modified continual reassessment scheme. The updated probabilities of DLT are calculated with a Gibbs sampler that employs a weighting mechanism to calibrate the influence of data vs the prior. At the end of the trial, we recommend one or more dose combinations as the MTD based on our proposed algorithm. We apply our method to a Phase I clinical trial of CB-839 and Gemcitabine that motivated this nonparametric design. The design operating characteristics indicate that our method is comparable with existing methods.

Nodal staging convergence for HPV- and HPV+ oropharyngeal carcinoma.

BACKGROUND: Modern disease staging systems have restructured human papillomavirus (HPV)-negative (HPV-) and HPV-positive (HPV+) oropharyngeal carcinoma (OPC) into distinct pathologic nodal systems. Given that quantitative lymph node (LN) burden is the dominant prognostic factor in most head and neck cancers, we investigated whether HPV- and HPV+ OPC warrant divergent pathologic nodal classification. METHODS: Multivariable Cox regression models of OPC surgical patients identified via U.S. cancer registry data were constructed to determine associations between survival and nodal characteristics. Nonlinear associations between metastatic LN number and survival were modeled with restricted cubic splines. Recursive partitioning analysis (RPA) was used to derive unbiased nodal schema. RESULTS: Mortality risk escalated continuously with each successive positive LN in both OPC subtypes, with analogous slope. Survival hazard increased by 18.5% (hazard ratio [HR], 1.19 [95% CI, 1.16-1.21]; P < .001) and 19.1% (HR, 1.19 [95% CI, 1.17-1.21]; P < .001), with each added positive LN for HPV- and HPV+ OPC, respectively, up to identical change points of 5 positive LNs. Extranodal extension (ENE) was an independent predictor of HPV- OPC (HR, 1.55 [95% CI, 1.20-1.99]; P < .001) and HPV+ OPC (HR 1.73 [95% CI, 1.36-2.20]; P < .001) mortality. In RPA for both diseases, metastatic LN was the principal nodal covariate driving survival, with ENE as a secondary determinant. Given the similarities across analyses, we propose a concise, unifying HPV-/HPV+ OPC pathologic nodal classification schema: N1, 1-5 LN+/ENE-; N2, 1-5 LN+/ENE+; N3, >5 LN+. CONCLUSION: HPV- and HPV+ OPC exhibit parallel relationships between nodal characteristics and relative mortality. In both diseases, metastatic LN number represents the principal nodal covariate governing survival, with ENE being an influential secondary element. A consolidated OPC pathologic nodal staging system that is based on these covariates may best convey prognosis. LAY SUMMARY: The current nodal staging system for oropharyngeal carcinoma (OPC) has divided human papillomavirus (HPV)-negative (HPV-) and HPV-positive (HPV+) OPC into distinct systems that rely upon criteria that establish them as separate entities, a complexity that may undermine the core objective of staging schema to clearly communicate prognosis. Our large-scale analysis revealed that HPV- and HPV+ pathologic nodal staging systems in fact mirror each other. Multiple analyses produced conspicuously similar nodal staging systems, with metastatic lymph node number and extranodal extension delineating the highest risk groups that shape prognosis. We propose unifying HPV- and HPV+ nodal systems to best streamline prognostication and maximize staging accuracy.

On the properties of the toxicity index and its statistical efficiency.

Cancer clinical trials typically generate detailed patient toxicity data. The most common measure used to summarize patient toxicity is the maximum grade among all toxicities and it does not fully represent the toxicity burden experienced by patients. In this article, we study the mathematical and statistical properties of the toxicity index (TI), in an effort to address this deficiency. We introduce a total ordering, (T-rank), that allows us to fully rank the patients according to how frequently they exhibit toxicities, and show that TI is the only measure that preserves the T-rank among its competitors. Moreover, we propose a Poisson-Limit model for sparse toxicity data. Under this model, we develop a general two-sample test, which can be applied to any summary measure for detecting differences among two population of toxicity data. We derive the asymptotic power function of this class as well as the asymptotic relative efficiency (ARE) of the members of the class. We evaluate the ARE formula empirically and show that if the data are drawn from a random Poisson-Limit model, the TI is more efficient, with high probability, than the maximum and the average summary measures. Finally, we evaluate our method on clinical trial toxicity data and show that TI has a higher power in detecting the differences in toxicity profile among treatments. The results of this article can be applied beyond toxicity modeling, to any problem where one observes a sparse array of scores on subjects and a ranking based on extreme scores is desirable.

Visualizing adverse events in clinical trials using correspondence analysis with R-package visae.

BACKGROUND: Graphical displays and data visualization are essential components of statistical analysis that can lead to improved understanding of clinical trial adverse event (AE) data. Correspondence analysis (CA) has been introduced decades ago as a multivariate technique that can communicate AE contingency tables using two-dimensional plots, while quantifying the loss of information as other dimension reduction techniques such as principal components and factor analysis. METHODS: We propose the application of stacked CA using contribution biplots as a tool to explore differences in AE data among treatments in clinical trials. We defined five levels of refinement for the analysis based on data derived from the Common Terminology Criteria for Adverse Events (CTCAE) grades, domains, terms and their combinations. In addition, we developed a Shiny app built in an R-package, visae, publicly available on Comprehensive R Archive Network (CRAN), to interactively investigate CA configurations based on the contribution to the explained variance and relative frequency of AEs. Data from two randomized controlled trials (RCT) were used to illustrate the proposed methods: NSABP R-04, a neoadjuvant rectal 2 × 2 factorial trial comparing radiation therapy with either capecitabine (Cape) or 5-fluorouracil (5-FU) alone with or without oxaliplatin (Oxa), and NSABP B-35, a double-blind RCT comparing tamoxifen to anastrozole in postmenopausal women with hormone-positive ductal carcinoma in situ. RESULTS: In the R04 trial (n = 1308), CA biplots displayed the discrepancies between single agent treatments and their combinations with Oxa at all levels of AE classes, such that these discrepancies were responsible for the largest portion of the explained variability among treatments. In addition, an interaction effect when adding Oxa to Cape/5-FU was identified when the distance between Cape+Oxa and 5-FU + Oxa was observed to be larger than the distance between 5-FU and Cape, with Cape+Oxa and 5-FU + Oxa in different quadrants of the CA biplots. In the B35 trial (n = 3009), CA biplots showed different patterns for non-adherent Anastrozole and Tamoxifen compared with their adherent counterparts. CONCLUSION: CA with contribution biplot is an effective tool that can be used to summarize AE data in a two-dimensional display while minimizing the loss of information and interpretation.

A phase I study of sirolimus in combination with metronomic therapy (CHOAnome) in children with recurrent or refractory solid and brain tumors.

BACKGROUND/PURPOSE: To determine the maximum tolerated dose, toxicities, and response of sirolimus combined with oral metronomic therapy in pediatric patients with recurrent and refractory solid and brain tumors. PROCEDURE: Patients younger than 30 years of age with recurrent, refractory, or high-risk solid and brain tumors were eligible. Patients received six-week cycles of sirolimus with twice daily celecoxib, and alternating etoposide and cyclophosphamide every three weeks, with Bayesian dose escalation over four dose levels (NCT01331135). RESULTS: Eighteen patients were enrolled: four on dose level (DL) 1, four on DL2, eight on DL3, and two on DL4. Diagnoses included solid tumors (Ewing sarcoma, osteosarcoma, malignant peripheral nerve sheath tumor, rhabdoid tumor, retinoblastoma) and brain tumors (glioblastoma multiforme [GBM], diffuse intrinsic pontine glioma, high-grade glioma [HGG], medulloblastoma, ependymoma, anaplastic astrocytoma, low-grade infiltrative astrocytoma, primitive neuroectodermal tumor, nongerminomatous germ cell tumor]. One dose-limiting toxicity (DLT; grade 4 neutropenia) was observed on DL2, two DLTs (grade 3 abdominal pain and grade 3 mucositis) on DL3, and two DLTs (grade 3 dehydration and grade 3 mucositis) on DL4. The recommended phase II dose of sirolimus was 2 mg/m2 (DL3). Best response was stable disease (SD) in eight patients, and partial response (PR) in one patient with GBM. A patient with HGG was removed from the study with SD and developed PR without further therapy. Western blot analysis showed inhibition of phospho-S6 kinase in all patients during the first cycle of therapy. CONCLUSION: The combination of sirolimus with metronomic chemotherapy is well tolerated in children. A phase II trial of this combination is ongoing.

A Bayesian seamless phase I-II trial design with two stages for cancer clinical trials with drug combinations.

The use of drug combinations in clinical trials is increasingly common during the last years since a more favorable therapeutic response may be obtained by combining drugs. In phase I clinical trials, most of the existing methodology recommends a one unique dose combination as "optimal," which may result in a subsequent failed phase II clinical trial since other dose combinations may present higher treatment efficacy for the same level of toxicity. We are particularly interested in the setting where it is necessary to wait a few cycles of therapy to observe an efficacy outcome and the phase I and II population of patients are different with respect to treatment efficacy. Under these circumstances, it is common practice to implement two-stage designs where a set of maximum tolerated dose combinations is selected in a first stage, and then studied in a second stage for treatment efficacy. In this article we present a new two-stage design for early phase clinical trials with drug combinations. In the first stage, binary toxicity data is used to guide the dose escalation and set the maximum tolerated dose combinations. In the second stage, we take the set of maximum tolerated dose combinations recommended from the first stage, which remains fixed along the entire second stage, and through adaptive randomization, we allocate subsequent cohorts of patients in dose combinations that are likely to have high posterior median time to progression. The methodology is assessed with extensive simulations and exemplified with a real trial.

Cancer phase I trial design using drug combinations when a fraction of dose limiting toxicities is attributable to one or more agents.

Drug combination trials are increasingly common nowadays in clinical research. However, very few methods have been developed to consider toxicity attributions in the dose escalation process. We are motivated by a trial in which the clinician is able to identify certain toxicities that can be attributed to one of the agents. We present a Bayesian adaptive design in which toxicity attributions are modeled via copula regression and the maximum tolerated dose (MTD) curve is estimated as a function of model parameters. The dose escalation algorithm uses cohorts of two patients, following the continual reassessment method (CRM) scheme, where at each stage of the trial, we search for the dose of one agent given the current dose of the other agent. The performance of the design is studied by evaluating its operating characteristics when the underlying model is either correctly specified or misspecified. We show that this method can be extended to accommodate discrete dose combinations.

Development of a novel salivary gland cancer lymph node staging system.

BACKGROUND: Current lymph node (LN) staging for salivary gland cancer (SGC) is extrapolated from mucosal head and neck squamous cell carcinoma. However, given its unique biology and clinical behavior, it is possible that a SGC-specific LN staging system would be more accurate. METHODS: Patients from the National Cancer Data Base with nonmetastatic SGC of the head and neck who were diagnosed from 2004 through 2013 and underwent surgical resection and neck dissection removing at least 10 LNs were included. Multivariable models were constructed to assess the association between survival and LN factors, including number of metastatic LNs, extranodal extension, LN size, and lower LN involvement. RESULTS: Overall, 4520 patients met the inclusion criteria. An increasing number of metastatic LNs was found to be strongly associated with worse survival without plateau. The risk of death increased more rapidly up to 4 LNs (hazard ratio, 1.34; 95% confidence interval, 1.27-1.41 [P < .001]), and was more gradual for additional LNs >4 (hazard ratio, 1.02; 95% confidence interval, 1.01-1.03 [P < .001]). LN size, extranodal extension, and lower LN involvement appeared to have no impact on survival when accounting for the number of metastatic LNs. Recursive partitioning analysis was used to create a novel SGC LN staging system in which N0 indicates 0 positive LNs, N1 indicates 1 to 2 positive LNs, N2 indicates 3 to 21 positive LNs, and N3 indicates ≥ 22 positive LNs. This system exhibited greater concordance than the current American Joint Committee on Cancer (eighth edition) system. CONCLUSIONS: Quantitative LN burden is an important determinant of survival in patients with SGC. Use of this variable may improve SGC staging. Cancer 2018. © 2018 American Cancer Society.

Quantitative survival impact of composite treatment delays in head and neck cancer.

BACKGROUND: Multidisciplinary management of head and neck cancer (HNC) must reconcile increasingly sophisticated subspecialty care with timeliness of care. Prior studies examined the individual effects of delays in diagnosis-to-treatment interval, postoperative interval, and radiation interval but did not consider them collectively. The objective of the current study was to investigate the combined impact of these interwoven intervals on patients with HNC. METHODS: Patients with HNC who underwent curative-intent surgery with radiation were identified in the National Cancer Database between 2004 and 2013. Multivariable models were constructed using restricted cubic splines to determine nonlinear relations with overall survival. RESULTS: Overall, 15,064 patients were evaluated. After adjustment for covariates, only prolonged postoperative interval (P < .001) and radiation interval (P < .001) independently predicted for worse outcomes, whereas the association of diagnosis-to-treatment interval with survival disappeared. By using multivariable restricted cubic spline functions, increasing postoperative interval did not affect mortality until 40 days after surgery, and each day of delay beyond this increased the risk of mortality until 70 days after surgery (hazard ratio, 1.14; 95% confidence interval, 1.01-1.28; P = .029). For radiation interval, mortality escalated continuously with each additional day of delay, plateauing at 55 days (hazard ratio, 1.25; 95% confidence interval, 1.11-1.41; P < .001). Delays beyond these change points were not associated with further survival decrements. CONCLUSIONS: Increasing delays in postoperative and radiation intervals are associated independently with an escalating risk of mortality that plateaus beyond certain thresholds. Delays in initiating therapy, conversely, are eclipsed in importance when appraised in conjunction with the entire treatment course. Such findings may redirect focus to streamlining those intervals that are most sensitive to delays when considering survival burden. Cancer 2018. © 2018 American Cancer Society.

A Bayesian adaptive design for cancer phase I trials using a flexible range of doses.

We present a Bayesian adaptive design for dose finding in cancer phase I clinical trials. The goal is to estimate the maximum tolerated dose (MTD) after possible modification of the dose range during the trial. Parametric models are used to describe the relationship between the dose and the probability of dose-limiting toxicity (DLT). We investigate model reparameterization in terms of the probabilities of DLT at the minimum and maximum available doses at the start of the trial. Trial design proceeds using escalation with overdose control (EWOC), where at each stage of the trial we seek the dose of the agent such that the posterior probability of exceeding the MTD of this agent is bounded by a feasibility bound. At any time during the trial, we test whether the MTD is below or above the minimum and maximum doses, respectively. If during the trial there is evidence that the MTD is outside the range of doses, we extend the range of doses and complete the trial with the planned sample size. At the end of the trial, a Bayes estimate of the MTD is proposed. We evaluate design operating characteristics in terms of safety of the trial design and efficiency of the MTD estimate under various scenarios and model misspecification. The methodology is further compared to the original EWOC design. We showed by comprehensive simulation studies that the proposed method is safe and can estimate the MTD more efficiently than the original EWOC design.

Treatment at high-volume facilities and academic centers is independently associated with improved survival in patients with locally advanced head and neck cancer.

BACKGROUND: The treatment of head and neck cancers is complex and associated with significant morbidity, requiring multidisciplinary care and physician expertise. Thus, facility characteristics, such as clinical volume and academic status, may influence outcomes. METHODS: The current study included 46,567 patients taken from the National Cancer Data Base who were diagnosed with locally advanced invasive squamous cell carcinomas of the oropharynx, larynx, and hypopharynx and were undergoing definitive radiotherapy. High-volume facilities (HVFs) were defined as the top 1% of centers by the number of patients treated from 2004 through 2012. Multivariable Cox regression and propensity score matching were performed to account for imbalances in covariates. RESULTS: The median follow-up was 55.1 months. Treatment at a HVF (hazard ratio, 0.798; 95% confidence interval, 0.753-0.845 [P<.001]) and treatment at an academic facility (hazard ratio, 0.897; 95% confidence interval, 0.871-0.923 [P<.001]) were found to be independently associated with improved overall survival in multivariable analysis. In propensity score-matched cohorts, the 5-year overall survival rate was 61.6% versus 55.5% for patients treated at an HVF versus lower-volume facilities, respectively (P<.001). Similarly, the 5-year overall survival rate was 52.3% versus 49.7% for patients treated at academic versus nonacademic facilities (P<.001). Analysis of facility volume as a continuous variable demonstrated continual improvement in survival with an increased number of patients treated. The impact of facility volume and academic designation on survival was observed when using a variety of thresholds to define HVF, and across the vast majority of subgroups, including both oropharyngeal and nonoropharyngeal subsites. CONCLUSIONS: Patients with locally advanced head and neck squamous cell carcinoma who are undergoing curative radiotherapy at HVFs and academic centers appear to have improved survival. Cancer 2017;123:3933-42. © 2017 American Cancer Society.

Combined high-intensity local treatment and systemic therapy in metastatic head and neck squamous cell carcinoma: An analysis of the National Cancer Data Base.

BACKGROUND: There is increasing evidence that primary tumor ablation can improve survival for some cancer patients with distant metastases. This may be particularly applicable to head and neck squamous cell carcinoma (HNSCC) because of its tropism for locoregional progression. METHODS: This study included patients with metastatic HNSCC undergoing systemic therapy identified in the National Cancer Data Base. High-intensity local treatment was defined as radiation doses ≥ 60 Gy or oncologic resection of the primary tumor. Multivariate Cox regression, propensity score matching, landmark analysis, and subgroup analysis were performed to account for imbalances in covariates, including adjustments for the number and location of metastatic sites in the subset of patients with this information available. RESULTS: In all, 3269 patients were included (median follow-up, 51.5 months). Patients undergoing systemic therapy with local treatment had improved survival in comparison with patients receiving systemic therapy alone in propensity score-matched cohorts (2-year overall survival, 34.2% vs 20.6%; P < .001). Improved survival was associated only with patients receiving high-intensity local treatment, whereas those receiving lower-intensity local treatment had survival similar to that of patients receiving systemic therapy without local treatment. The impact of high-intensity local therapy was time-dependent, with a stronger impact within the first 6 months after the diagnosis (adjusted hazard ratio [AHR], 0.255; 95% confidence interval [CI], 0.210-0.309; P < .001) in comparison with more than 6 months after the diagnosis (AHR, 0.622; 95% CI, 0.561-0.689; P < .001) in the multivariate analysis. A benefit was seen in all subgroups, in landmark analyses of 1-, 2-, and 3-year survivors, and when adjusting for the number and location of metastatic sites. CONCLUSIONS: Aggressive local treatment warrants prospective evaluation for select patients with metastatic HNSCC. Cancer 2017;123:4583-4593. © 2017 American Cancer Society.

Impact of concomitant chemoradiation on survival for patients with T1-2N1 head and neck cancer.

BACKGROUND: Single-modality radiotherapy is considered a standard-of-care option for certain stage III, T1-2N1 head and neck squamous cell carcinomas (HNSCCs). The role of concomitant chemoradiation is not well established because there have been no studies comparing chemoradiation with radiation alone in this population. METHODS: This study analyzed patients in the National Cancer Data Base with cT1-2N1M0 invasive squamous cell carcinomas of the oropharynx, larynx, and hypopharynx who were diagnosed between 2004 and 2012 and were undergoing definitive radiation. Patients who were undergoing surgery before radiation with unknown follow-up or for whom either the receipt or timing of chemotherapy was unknown were excluded. RESULTS: In all, 5030 patients with T1-2N1 oropharyngeal, laryngeal, or hypopharyngeal cancer were included. The median follow-up was 56.8 months (95% confidence interval [CI], 55.7-58.6 months). Overall, 68% of the patients received concomitant chemoradiation (CCRT). The use of CCRT significantly increased during the time period of this study from 53% in 2004 to 78% in 2012 (P < .001). CCRT was associated with improved overall survival (OS) in comparison with radiation alone in a multivariate analysis (hazard ratio [HR], 0.80; 95% CI, 0.72-0.88; P < .001). In propensity score-adjusted analyses, CCRT remained significantly associated with improved OS, with 5-year OS rates of 63.5% (95% CI, 60.7%-66.2%) and 55.6% (95% CI, 52.7%-58.4%; P < .001) with CCRT and radiation alone, respectively. Subgroup analyses showed a benefit across the majority of subgroups, including patients with oropharyngeal cancer (HR, 0.74; 95% CI, 0.65-0.85; P < .001). CONCLUSIONS: Concomitant chemoradiation is associated with improved survival for patients with T1-2N1 HNSCC. Prospective trials in this population should be pursued. Cancer 2017;123:1555-1565. © 2017 American Cancer Society.

A Bayesian adaptive design for estimating the maximum tolerated dose curve using drug combinations in cancer phase I clinical trials.

We present a cancer phase I clinical trial design of a combination of two drugs with the goal of estimating the maximum tolerated dose curve in the two-dimensional Cartesian plane. A parametric model is used to describe the relationship between the doses of the two agents and the probability of dose limiting toxicity. The model is re-parameterized in terms of the probabilities of toxicities at dose combinations corresponding to the minimum and maximum doses available in the trial and the interaction parameter. Trial design proceeds using cohorts of two patients receiving doses according to univariate escalation with overdose control (EWOC), where at each stage of the trial, we seek a dose of one agent using the current posterior distribution of the MTD of this agent given the current dose of the other agent. The maximum tolerated dose curve is estimated as a function of Bayes estimates of the model parameters. Performance of the trial is studied by evaluating its design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD curve and under model misspecifications for the true dose-toxicity relationship. The method is further extended to accommodate discrete dose combinations and compared with previous approaches under several scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Escalation with Overdose Control is More Efficient and Safer than Accelerated Titration for Dose Finding.

The standard 3 + 3 or "modified Fibonacci" up-and-down (MF-UD) method of dose escalation is by far the most used design in dose-finding cancer trials. However, MF-UD has always shown inferior performance when compared with its competitors regarding number of patients treated at optimal doses. A consequence of using less effective designs is that more patients are treated with doses outside the therapeutic window. In June 2012, the U S Food and Drug Administration (FDA) rejected the proposal to use Escalation with Overdose Control (EWOC), an established dose-finding method which has been extensively used in FDA-approved first in human trials and imposed a variation of the MF-UD, known as accelerated titration (AT) design. This event motivated us to perform an extensive simulation study comparing the operating characteristics of AT and EWOC. We show that the AT design has poor operating characteristics relative to three versions of EWOC under several practical scenarios. From the clinical investigator's perspective, lower bias and mean square error make EWOC designs preferable than AT designs without compromising safety. From a patient's perspective, uniformly higher proportion of patients receiving doses within an optimal range of the true MTD makes EWOC designs preferable than AT designs.

Dose finding with drug combinations in cancer phase I clinical trials using conditional escalation with overdose control.

We present a Bayesian adaptive design for dose finding of a combination of two drugs in cancer phase I clinical trials. The goal is to estimate the maximum tolerated dose (MTD) as a curve in the two-dimensional Cartesian plane. We use a logistic model to describe the relationship between the doses of the two agents and the probability of dose limiting toxicity. The model is re-parameterized in terms of parameters clinicians can easily interpret. Trial design proceeds using univariate escalation with overdose control, where at each stage of the trial, we seek a dose of one agent using the current posterior distribution of the MTD of this agent given the current dose of the other agent. At the end of the trial, an estimate of the MTD curve is proposed as a function of Bayes estimates of the model parameters. We evaluate design operating characteristics in terms of safety of the trial design and percent of dose recommendation at dose combination neighborhoods around the true MTD curve. We also examine the performance of the approach under model misspecifications for the true dose-toxicity relationship.