The value of source data verification in a cancer clinical trial

Background Source data verification (SDV) is a resource intensive method of quality assurance frequently used in clinical trials. There is no empirical evidence to suggest that SDV would impact on comparative treatment effect results from a clinical trial. Methods Data discrepancies and comparative treatment effects obtained following 100% SDV were compared to those based on data without SDV. Overall survival (OS) and Progression-free survival (PFS) were compared using Kaplan-Meier curves, log-rank tests and Cox models. Tumour response classifications and comparative treatment Odds Ratios (ORs) for the outcome objective response rate, and number of Serious Adverse Events (SAEs) were compared. OS estimates based on SDV data were compared against estimates obtained from centrally monitored data. Findings Data discrepancies were identified between different monitoring procedures for the majority of variables examined, with some variation in discrepancy rates. There were no systematic patterns to discrepancies and their impact was negligible on OS, the primary outcome of the trial (HR (95% CI): 1.18(0.99 to 1.41), p = 0.064 with 100% SDV; 1.18(0.99 to 1.42), p = 0.068 without SDV; 1.18(0.99 to 1.40), p = 0.073 with central monitoring). Results were similar for PFS. More extreme discrepancies were found for the subjective outcome overall objective response (OR (95% CI): 1.67(1.04 to 2.68), p = 0.03 with 100% SDV; 2.45(1.49 to 4.04), p = 0.0003 without any SDV) which was mostly due to differing CT scans. Interpretation Quality assurance methods used in clinical trials should be informed by empirical evidence. In this empirical comparison, SDV was expensive and identified random errors that made little impact on results and clinical conclusions of the trial. Central monitoring using an external data source was a more efficient approach for the primary outcome of OS. For the subjective outcome objective response, an independent blinded review committee and tracking system to monitor missing scan data could be more efficient than SDV

Osteoblastic flare in a patient with advanced gastric cancer after treatment with pemetrexed and oxaliplatin: implications for response assessment with RECIST criteria

<p>Abstract</p> <p>Background</p> <p>The RECIST guidelines are commonly used in phase II and III clinical trials. The correct definition of response can be controversial in some situations, as in the case we describe.</p> <p>Case presentation</p> <p>A 43 year-old man with advanced gastric cancer was enrolled in a phase II trial where he was treated with pemetrexed 500 mg/m²plus oxaliplatin 120 mg/m²every 3 weeks. At baseline, the target lesions were lymph-nodes, and the non-target lesions were small pulmonary nodules. At first re-evaluation, the target lesions showed partial response and the non-target lesions showed complete response, but new diffuse osteoblastic lesions appeared. The investigator decided to continue treatment until the second re-evaluation. CT scan confirmed the response of the target and non-target lesions, while the osteoblastic lesions did not change.</p> <p>Conclusion</p> <p>The appearance of osteoblastic lesions after an active antitumor treatment, a phenomenon known as flare, can complicate the definition of the best overall response using RECIST criteria. This possibility should be considered by oncologists involved in clinical trials.</p

Determination of an optimal response cut-off able to predict progression-free survival in patients with well-differentiated advanced pancreatic neuroendocrine tumours treated with sunitinib: an alternative to the current RECIST-defined response.

BACKGROUND: Sunitinib prolongs progression-free survival (PFS) in patients with advanced pancreatic neuroendocrine tumours (pNET). Response Evaluation Criteria in Solid Tumors (RECIST)-defined partial responses (PR; classically defined as ⩾30% size decrease from baseline) are infrequent. METHODS: Individual data of pNET patients from the phase II [NCT00056693] and pivotal phase III [NCT00428597] trials of sunitinib were analysed in this investigator-initiated, post hoc study. The primary objective was to determine the optimal RECIST (v.1.0) response cut-off value to identify patients who were progression-free at 11 months (median PFS in phase III trial); and the most informative time-point (highest area under the curve (AUC) by receiver operating characteristic (ROC) analysis and logistic regression) for prediction of benefit (PFS) from sunitinib. RESULTS: Data for 237 patients (85 placebo; 152 sunitinib (n=66.50 mg \u274-weeks on/2-weeks off\u27 schedule; n=86 \u2737.5 mg continuous daily dosing (CDD)\u27)) and 788 scans were analysed. The median PFS for sunitinib and placebo were 9.3 months (95% CI 7.6-12.2) and 5.4 months (95% CI 3.5-6.01), respectively (hazard ratio (HR) 0.43 (95% CI 0.29-0.62); P CONCLUSIONS: A 10% reduction within marker lesions identifies pNET patients benefiting from sunitinib treatment with implications for maintenance of dose intensity and future trial design

Locally advanced/inflammatory breast cancers treated with intensive epirubicin-based neoadjuvant chemotherapy: are there molecular markers in the primary tumour that predict for 5-year clinical outcome?

Background: Locally advanced and/or inflammatory breast cancer (LABC) is a heterogeneous disease. Molecular markers may help to understand this heterogeneity. This paper reports the results of a study assessing the potential prognostic or predictive value of HER-2, p53, cyclinD1, MIB1, ER and PgR expression by immunohistochemistry from patients included in an EORTC-NCIC-SAKK trial. Patients and methods: A total of 448 patients with a cytological or histological diagnosis of LABC were randomised into a trial comparing two anthracycline-based neoadjuvant regimens. Chemotherapy was followed by standard locoregional therapy. Survival was comparable in both arms. We collected and analysed centrally paraffin-embedded tumour specimens from 187 (72.5%) of 258 patients that had a histological diagnosis. Results: Of the patients included in this molecular marker study 114 relapsed and 91 died. In the multivariate analysis p53 positivity was associated with a shorter progression-free survival [hazard ratio (HR) = 1.96; 95% CI 1.33-2.91; P = 0.0008) and a shorter overall survival (HR = 1.98; 95% CI 1.28-3.06; P = 0.002). PgR positivity predicted for a longer overall survival (HR = 0.54; 95% CI 0.35-0.83; P = 0.0045). Conclusions: p53 was an independent factor predicting for survival. In order to clarify whether p53 is a pure prognostic and/or a predictive factor, a phase III trial is being conducted (EORTC 10994/BIG 00-01 study) using functional assay in yeast from frozen tumour sample

Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

Background Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response. Methods Eighteen patients (age range, 1.9–20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1–16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM). Results Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η2 = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis. Conclusions We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols

Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT)

Background: Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. Patients and methods: An open-label prospective phase II trial ('PREDICT') in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Results: Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS +). The 1-year OS rate was 83.1%/83.3% in the GS+/GS- populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS- patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS-). There was one complete response (GS-) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Conclusion: Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS- and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study. This study is registered at www.clinicatrials.gov NCT00942162

Optimizing CIGB-300 intralesional delivery in locally advanced cervical cancer

Background:We conducted a phase 1 trial in patients with locally advanced cervical cancer by injecting 0.5 ml of the CK2-antagonist CIGB-300 in two different sites on tumours to assess tumour uptake, safety, pharmacodynamic activity and identify the recommended dose.Methods:Fourteen patients were treated with intralesional injections containing 35 or 70 mg of CIGB-300 in three alternate cycles of three consecutive days each before standard chemoradiotherapy. Tumour uptake was determined using 99 Tc-radiolabelled peptide. In situ B23/nucleophosmin was determined by immunohistochemistry.Results:Maximum tumour uptake for CIGB-300 70-mg dose was significantly higher than the one observed for 35 mg: 16.1±8.9 vs 31.3±12.9 mg (P=0.01). Both, AUC 24h and biological half-life were also significantly higher using 70 mg of CIGB-300 (P<0.001). Unincorporated CIGB-300 diffused rapidly to blood and was mainly distributed towards kidneys, and marginally in liver, lungs, heart and spleen. There was no DLT and moderate allergic-like reactions were the most common systemic side effect with strong correlation between unincorporated CIGB-300 and histamine levels in blood. CIGB-300, 70 mg, downregulated B23/nucleophosmin (P=0.03) in tumour specimens.Conclusion:Intralesional injections of 70 mg CIGB-300 in two sites (0.5 ml per injection) and this treatment plan are recommended to be evaluated in phase 2 studies.Fil: Sarduy, M. R.. Medical-surgical Research Center; CubaFil: García, I.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Coca, M. A.. Clinical Investigation Center; CubaFil: Perera, A.. Clinical Investigation Center; CubaFil: Torres, L. A.. Clinical Investigation Center; CubaFil: Valenzuela, C. M.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Baladrón, I.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Solares, M.. Hospital Materno Ramón González Coro; CubaFil: Reyes, V.. Center For Genetic Engineering And Biotechnology Havana; CubaFil: Hernández, I.. Isotope Center; CubaFil: Perera, Y.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Martínez, Y. M.. Medical-surgical Research Center; CubaFil: Molina, L.. Medical-surgical Research Center; CubaFil: González, Y. M.. Medical-surgical Research Center; CubaFil: Ancízar, J. A.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Prats, A.. Clinical Investigation Center; CubaFil: González, L.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Casacó, C. A.. Clinical Investigation Center; CubaFil: Acevedo, B. E.. Centro de Ingeniería Genética y Biotecnología; CubaFil: López Saura, P. A.. Centro de Ingeniería Genética y Biotecnología; CubaFil: Alonso, Daniel Fernando. Universidad Nacional de Quilmes; ArgentinaFil: Gómez, R.. Elea Laboratories; ArgentinaFil: Perea Rodríguez, S. E.. Center For Genetic Engineering And Biotechnology Havana; Cuba. Centro de Ingeniería Genética y Biotecnología; Cub