Open-label, clinical phase I studies of tasquinimod in patients with castration-resistant prostate cancer

Background:Tasquinimod is a quinoline-3-carboxamide derivative with anti-angiogenic activity. Two open-label phase I clinical trials in patients were conducted to evaluate the safety and tolerability of tasquinimod, with additional pharmacokinetic and efficacy assessments.Methods:Patients with castration-resistant prostate cancer with no previous chemotherapy were enrolled in this study. The patients received tasquinimod up to 1 year either at fixed doses of 0.5 or 1.0 mg per day or at an initial dose of 0.25 mg per day that escalated to 1.0 mg per day.Results:A total of 32 patients were enrolled; 21 patients were maintained for >/=4 months. The maximum tolerated dose was determined to be 0.5 mg per day; but when using stepwise intra-patient dose escalation, a dose of 1.0 mg per day was well tolerated. The dose-limiting toxicity was sinus tachycardia and asymptomatic elevation in amylase. Common treatment-emergent adverse events included transient laboratory abnormalities, anaemia, nausea, fatigue, myalgia and pain. A serum prostate-specific antigen (PSA) decline of >/=50% was noted in two patients. The median time to PSA progression (>25%) was 19 weeks. Only 3 out of 15 patients (median time on study: 34 weeks) developed new bone lesions.Conclusion:Long-term continuous oral administration of tasquinimod seems to be safe, and the overall efficacy results indicate that tasquinimod might delay disease progression.British Journal of Cancer advance online publication, 15 September 2009; doi:10.1038/sj.bjc.6605322 www.bjcancer.com

Predictive factors for skeletal complications in hormone-refractory prostate cancer patients with metastatic bone disease

Factors predictive of skeletal-related events (SREs) in bone metastatic prostate cancer patients with hormone-refractory disease were investigated. We evaluated the frequency of SREs in 200 hormone-refractory patients consecutively observed at our Institution and followed until death or the last follow-up. Baseline parameters were evaluated in univariate and multivariate analysis as potential predictive factors of SREs. Skeletal-related events were observed in 86 patients (43.0%), 10 of which (5.0%) occurred before the onset of hormone-refractory disease. In univariate analysis, patient performance status (P=0.002), disease extent (DE) in bone (P=0.0001), bone pain (P=0.0001), serum alkaline phosphatase (P=0.0001) and urinary N-telopeptide of type one collagen (P=0.0001) directly correlated with a greater risk to develop SREs, whereas Gleason score at diagnosis, serum PSA, Hb, serum albumin, serum calcium, types of bone lesions and duration of androgen deprivation therapy did not. Both DE in bone (hazard ratio (HR): 1.16, 95% confidence interval (CI): 1.07–1.25, P=0.000) and pain score (HR: 1.13, 95% CI: 1.06–1.20, P=0.000) were independent variables predicting for the onset of SREs in multivariate analysis. In patients with heavy tumour load in bone and great bone pain, the percentage of SREs was almost twice as high as (26 vs 52%, P<0.02) and occurred significantly earlier (P=0.000) than SREs in patients with limited DE in bone and low pain. Bone pain and DE in bone independently predict the occurrence of SREs in bone metastatic prostate cancer patients with hormone-refractory disease. These findings could help physicians in tailoring the skeletal follow-up most appropriate to individual patients and may prove useful for stratifying patients enrolled in bisphosphonate clinical trials

Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS). prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients

A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology

Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients.We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems.The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the proposed methodology towards automated detection of interaction effects, multi-class decision support systems, prognosis and high-dimensional data

Issues in applying multi-arm multi-stage methodology to a clinical trial in prostate cancer: the MRC STAMPEDE trial

Background: The multi-arm multi-stage (MAMS) trial is a new paradigm for conducting randomised controlled trials that allows the simultaneous assessment of a number of research treatments against a single control arm. MAMS trials provide earlier answers and are potentially more cost-effective than a series of traditionally designed trials. Prostate cancer is the most common tumour in men and there is a need to improve outcomes for men with hormone-sensitive, advanced disease as quickly as possible. The MAMS design will potentially facilitate evaluation and testing of new therapies in this and other diseases.Methods: STAMPEDE is an open-label, 5-stage, 6-arm randomised controlled trial using MAMS methodology for men with prostate cancer. It is the first trial of this design to use multiple arms and stages synchronously.Results: The practical and statistical issues faced by STAMPEDE in implementing MAMS methodology are discussed and contrasted with those for traditional trials. These issues include the choice of intermediate and final outcome measures, sample size calculations and the impact of varying the assumptions, the process for moving between trial stages, stopping accrual to each trial arm and overall, and issues around perceived trial complexity.Conclusion: It is possible to use the MAMS design to initiate and undertake large scale cancer trials. The results from STAMPEDE will not be known for some years but the lessons learned from running a MAMS trial are shared in the hope that other researchers will use this exciting and efficient method to perform further randomised controlled trials

Long-term benefit of sunitinib in patients with metastatic renal cell carcinoma in Latin America: retrospective analysis of patient clinical characteristics

Oren Smaletz,1 Matias Chac&oacute;n,2 Ludmila de Oliveira Koch,1 Daniela R de Carvalho Rocha,1 Fernanda C Cardoso1 1Department of Oncology, Hospital Israelita Albert Einstein, S&atilde;o Paulo, Brazil; 2Medical Oncology Department, Alexander Fleming Institute, Buenos Aires, Argentina Objective: To describe the clinical characteristics of Latin American patients with metastatic renal cell carcinoma (mRCC) who experienced a progression-free survival (PFS) for at least 15 months following treatment with sunitinib. Patients and methods: In this retrospective analysis, mRCC patients in two institutions in Latin America received sunitinib at a starting dose of either 50 mg/day for 4 weeks followed by 2 weeks off treatment (Schedule 4/2) in repeated 6-week cycles or sunitinib 37.5 mg on a continuous daily dosing schedule. Clinical characteristics, tolerability, and PFS data were collected. Results: Twenty-nine patients with long-term clinical benefit from sunitinib were identified between September 2005 and August 2009. Median PFS was 23 months (range: 15&ndash;54 months). Two of the 29 patients with prolonged PFS achieved a complete response and additional eleven had a partial response. Most patients were aged &lt;60 years, had good performance status, favorable or intermediate Memorial Sloan Kettering Cancer Center prognostic risk, and disease limited to one or two sites. Dose reduction was necessary in all patients who started sunitinib at 50 mg/day administered on Schedule 4/2. Adverse events leading to dose reduction included grade 3 hand&ndash;foot syndrome, mucositis, fatigue, and hypertension. At the time of data cutoff, four patients were still receiving sunitinib treatment. Conclusion: Extended PFS can be achieved in Latin American patients with mRCC treated with sunitinib. Although the small sample size and retrospective nature of this evaluation preclude the identification of pretreatment predictive factors contributing to this benefit, the current analysis warrants further investigation using a larger data set in this population. Keywords: renal cell carcinoma, sunitinib, long-term benefit, Latin Americ