Statistical innovations in diagnostic device evaluation.

Due to rapid technological development, innovations in diagnostic devices are proceeding at an extremely fast pace. Accordingly, the needs for adopting innovative statistical methods have emerged in the evaluation of diagnostic devices. Statisticians in the Center for Devices and Radiological Health at the Food and Drug Administration have provided leadership in implementing statistical innovations. The innovations discussed in this article include: the adoption of bootstrap and Jackknife methods, the implementation of appropriate multiple reader multiple case study design, the application of robustness analyses for missing data, and the development of study designs and data analyses for companion diagnostics.

Distinctive clinical characteristics of malignant mesothelioma in young patients.

Although considered a disease of the elderly, a subset of patients with mesothelioma are young (<40 years). The goal of this study was to understand their characteristics and outcomes. The Surveillance, Epidemiology, and End Results (SEER) database was used to extract mesothelioma cases (1990-2010). We modeled Kaplan-Meyer survival curves stratified by site of disease, and age of presentation. 2% (207 of 12345) of mesothelioma patients are young. Sex distribution is comparable among the young (51% males, 49% females); males predominated (78%, 22%) in the older cohort. Frequency of pleural and peritoneal mesothelioma are similar in the young (47%, 48% respectively); pleural disease predominated in the old (90%, 9%). Cancer-directed surgeries are more frequent in the young. Regardless of histologic subtype, young patients with pleural (11 vs. 8 months) and peritoneal (not reached vs. 10 months) mesothelioma had significantly improved overall survival. In multivariate analysis, younger age was an independent prognostic factor. Although rare, mesothelioma do occur in the young; their characteristics are distinct from those of older patients. Further studies are needed to understand the interplay between genetic susceptibility and mineral fiber carcinogenesis in the pathogenesis of mesothelioma in the young.

Trends and Characteristics of Young Non-Small Cell Lung Cancer Patients in the United States.

BACKGROUND: Although the median age at diagnosis of non-small cell lung cancer (NSCLC) is 70 years, a subset of patients with NSCLC present at a younger age (<40 years). Little is known about the time-trends in incidence of NSCLC in the young, their characteristics and outcomes. METHODS: The surveillance, epidemiology, and end results database was used to extract NSCLC cases from 1978 to 2010. Yearly incidence rates in various age groups, race, site of disease, histology, treatment patterns, and outcomes were assessed. We modeled Kaplan-Meyer survival curves stratified by age of presentation. RESULTS: Young patients represented 0.6% of incident NSCLC from 1978 to 2010. The incidence of young NSCLC declined significantly during this time-period. Young NSCLCs had a higher proportion of women (51%), Asians or Pacific Islanders (14%), adenocarcinoma histology (59%) and were more likely to present with distant metastases (68%). The young had better all cause and lung cancer-specific survival than the older patients (median survival for localized, regional, and distant disease: not reached, 28, 9 vs. 46, 17, 5 months; p < 0.001 for all groups). Male sex, non-adenocarcinoma histology, and main bronchial primary were independent negative prognostic factors among the young. In contrast to the overall population, black race was a poor prognostic factor among the young. CONCLUSION: The incidence of NSCLC in the young decreased from 1978 to 2010. The clinical characteristics of NSCLC in the young, including demographic distribution, treatment, and outcomes are different from those observed in the older patients.

The impact of companion diagnostic device measurement performance on clinical validation of personalized medicine.

A key component of personalized medicine is companion diagnostics that measure biomarkers, for example, protein expression, gene amplification or specific mutations. Most of the recent attention concerning molecular cancer diagnostics has been focused on the biomarkers of response to therapy, such as V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in metastatic colorectal cancer, epidermal growth factor receptor mutations in metastatic malignant melanoma. The presence or absence of these markers is directly linked to the response rates of particular targeted therapies with small-molecule kinase inhibitors or antibodies. Therefore, testing for these markers has become a critical step in the target therapy of the aforementioned tumors. The core capability of personalized medicine is the companion diagnostic devices' (CDx) ability to accurately and precisely stratify patients by their likelihood of benefit (or harm) from a particular therapy. There is no reference in the literature discussing the impact of device's measurement performance, for example, analytical accuracy and precision on treatment effects, variances, and sample sizes of clinical trial for the personalized medicine. In this paper, using both analytical and estimation method, we assessed the impact of CDx measurement performance as a function of positive and negative predictive values and imprecision (standard deviation) on treatment effects, variances of clinical outcome, and sample sizes for the clinical trials.

Efficient experimental design and nonparametric modeling of drug interaction.

The design and analysis of drug combination studies continue to be an area requiring further methodological developments. Faessel et al. (1998) studied the joint effects of the combinations of trimetrexate (TMQ) and the GARFT inhibitor AG2034 to inhibit the growth of HCT-8 human ileocecal adenocarcinoma cells. Their experiments provide a rich data resource to validate the performance of new experimental design and analysis methods for future experiments. In this paper, we first re-analyze the same data with a nonparametric model and briefly review the experimental design used in the original paper. By comparing the analysis results, we found that the fixed ratio design and the usage of the parametric model for estimating the interaction index are based on an assumption not supported by the data. We then show how the efficiency of the experiments would be improved had the maximal power experimental design based on uniform measures been used. The usage of the proposed maximal power experimental design is further supported by simulation studies.