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Carmen Allegra

Publications and source records attributed to Carmen Allegra.

7 recordsLinked to original sources
PubMed2006

How do U.S. medical oncologists learn and apply new clinical trials information from press releases in nonmedical media? A case study based on ECOG 4599.

BACKGROUND: Practicing oncologists are expected to easily assimilate large amounts of rapidly evolving clinical data. We hypothesized that U.S. oncologists rapidly familiarize themselves with new, practice-relevant, phase III clinical trial data. We tested this hypothesis in relation to the release of phase III data from the Eastern Cooperative Oncology Group 4599 trial on the role of bevacizumab in advanced non-small cell lung cancer (NSCLC). METHODS: We queried approximately 310 medical oncologists concerning their awareness of the bevacizumab data within 1 and 3 weeks after the data release or immediately after the 2005 Annual Meeting of the American Society of Clinical Oncology (ASCO). RESULTS: Prior to the ASCO meeting, 57% and 56% of the oncologists in the two research meetings, respectively, indicated "awareness" of the data release. Less than 25% selected an accurate descriptor of the released information from a short list of plausible options. After the ASCO meeting, the figures were 88% and 34%. Over 50% said they plan to use bevacizumab in NSCLC treatment as soon as reimbursement is secure. Eighty-two percent said they plan to use it in second- or third-line treatment; 56% said they plan to use it during second-line chemotherapy despite progression during first-line use. A large majority intend to use bevacizumab in dosages, tumor types, drug combinations, and/or patients not specifically supported by phase III data. CONCLUSION: Release of clinically relevant phase III data through electronic and print media is a poor vehicle for informing U.S. medical oncologists. For a commercially available agent, this can have important implications for potential use in untested and potentially unsafe clinical settings. Effective educational strategies for dealing with the new paradigm of "instant" release of clinical data need to be developed.

Antibodies, Monoclonal↗
PubMed2005

Clinical trial designs for predictive marker validation in cancer treatment trials.

Current staging and risk-stratification methods in oncology, while helpful, fail to adequately predict malignancy aggressiveness and/or response to specific treatment. Increased knowledge of cancer biology is generating promising marker candidates for more accurate diagnosis, prognosis assessment, and therapeutic targeting. To apply these exciting results to maximize patient benefit, a disciplined application of well-designed clinical trials for assessing the utility of markers should be used. In this article, we first review the major issues to consider when designing a clinical trial assessing the usefulness of a predictive marker. We then present two classes of clinical trial designs: the Marker by Treatment Interaction Design and the Marker-Based Strategy Design. In the first design, we assume that the marker splits the population into groups in which the efficacy of a particular treatment will differ. This design can be viewed as a classical randomized clinical trial with upfront stratification for the marker. In the second design, after the marker status is known, each patient is randomly assigned either to have therapy determined by their marker status or to receive therapy independent of marker status. The predictive value of the marker is assessed by comparing the outcome of all patients in the marker-based arm to that of all of the patients in the non-marker-based arm. We present detailed sample size calculations for a specific clinical scenario. We discuss the advantages and disadvantages of the two trial designs and their appropriateness to specific clinical situations to assist investigators seeking to design rigorous, marker-based clinical trials.

Biomarkers, Tumor↗
PubMed2004

Thymidylate synthase as an oncogene: a novel role for an essential DNA synthesis enzyme.

Thymidylate synthase (TS) is an E2F1-regulated enzyme that is essential for DNA synthesis and repair. TS protein and mRNA levels are elevated in many human cancers, and high TS levels have been correlated with poor prognosis in patients with colorectal, breast, cervical, bladder, kidney, and non-small cell lung cancers. In this study, we show that ectopic expression of catalytically active TS is sufficient to induce a transformed phenotype in mammalian cells as manifested by foci formation, anchorage independent growth, and tumor formation in nude mice. In contrast, comparable levels of two TS mutants carrying single point mutations within the catalytic domain had no transforming activity. In addition, we show that overexpression of TS results in apoptotic cell death following serum removal. These data demonstrate that TS exhibits oncogene-like activity and suggest a link between TS-regulated DNA synthesis and the induction of a neoplastic phenotype.

Animals↗
PubMed2002

Issues in clinical trial design for tumor marker studies.

Scientific inquiry into the discovery, development, and application of tumor markers is proceeding rapidly. Despite this explosion in research and interest, the design of studies to formally assess the value of tumor markers in clinical practice is inconsistent and immature. Indeed, few markers have been widely accepted into standard clinical practice. Many issues must be prospectively considered in a methodical, systematic, and scientific fashion if progress is to be made in the development of validated tests that will have value in the management of patients with cancer. The purpose of this report is to present a discussion of the issues involved in designing clinical studies of putative tumor markers which provide sufficient data to result in the incorporation of the marker into clinical practice. We will focus on the design of studies to demonstrate and validate the clinical utility of both prognostic and predictive markers. Topics to be covered include issues of patient and sample heterogeneity, the prevalence of the marker, the sample capture rate, and the choice of endpoints. This will be followed by explicit consideration of study design, specifically the trial randomization schema for both prognostic and predictive factor studies.

Biomarkers, Tumor↗