Biomedical subjects

Marco Bonetti

Publications and source records attributed to Marco Bonetti.

9 recordsLinked to original sources

PubMed2007

Effect of glutathione S-transferase polymorphisms and proximity to hazardous waste sites on time to systemic lupus erythematosus diagnosis: results from the Roxbury lupus project.

OBJECTIVE: The high prevalence of systemic lupus erythematosus (SLE) among African American women may be due to environmental exposures, genetic factors, or a combination of factors. Our goal was to assess association of residential proximity to hazardous waste sites and genetic variation in 3 glutathione Stransferase (GST) genes (GSTM1, GSTT1, and GSTP1) with age at diagnosis of SLE. METHODS: Residential histories were obtained by interviewing 93 SLE patients from 3 predominantly African American neighborhoods in Boston. Residential addresses and locations of 416 hazardous waste sites in the study area were geocoded using ArcView software. Time-varying Cox models were used to study the effect of residential proximity to hazardous sites, GST genotype, and interaction between genotype and exposure in determining age at diagnosis. RESULTS: The prevalence of SLE among African American women in these neighborhoods was 3.56 SLE cases per 1,000. Homozygosity for GSTM1-null and GSTP1 Ile105Val in combination was associated with earlier SLE diagnosis (P = 0.03), but there was no association with proximity to 416 hazardous sites. Available data on specific site contaminants suggested that, at a subset of 67 sites, there was higher potential risk for exposure to volatile organic compounds (P < 0.05 with Bonferroni correction). GST genotypes had a significant interaction with proximity (P = 0.03) in analyses limited to these sites. CONCLUSION: There was no independent association between residential proximity to hazardous waste sites and the risk of earlier SLE diagnosis in this urban population. However, analysis of a limited number of sites indicated that the risk of earlier SLE associated with proximity to hazardous sites might be modulated by GST polymorphisms.

Adolescent↗

PubMed2006

Modelling menstrual status during and after adjuvant treatment for breast cancer.

Failure time data may consist of the observation of an event whose cause is unknown due to the censoring or lack of a second event that could identify the cause of the first event. Standard competing-risks methodology does not apply to this setting because the cause of the event is not always identifiable. Moreover, one cannot assume that the entire population will eventually experience the event of interest, and the observation is potentially censored for all patients. The model that we describe in this article is motivated by a breast cancer clinical trial conducted by the International Breast Cancer Study Group (IBCSG). Because some breast cancer adjuvant treatments for premenopausal patients who have undergone surgery cause the interruption of menses, or amenorrhoea, it is of interest to describe the process by which menses discontinue and resume after treatment is completed. The process is complicated by the fact that natural menopause also occurs in the patient population, and that treatment-induced amenorrhoea is not distinguishable from menopause unless menses are observed to resume after treatment completion. We discuss a parametric model for the time to amenorrhoea and for the time to the recovery of menses, also accounting for the presence of censoring and for the possibility that treatment causes an anticipation of natural menopause.

Adult↗

PubMed2005

Prognostic value of extracapsular tumor spread for locoregional control in premenopausal patients with node-positive breast cancer treated with classical cyclophosphamide, methotrexate, and fluorouracil: long-term observations from International Breast Cancer Study Group Trial VI.

PURPOSE: We sought to determine retrospectively whether extracapsular spread (ECS) might identify a subgroup that could benefit from radiotherapy after mastectomy, especially patients with 1 to 3 positive lymph nodes (LN1-3+). PATIENTS AND METHODS: We randomized 1,475 premenopausal women with node-positive breast cancer to three, six, or nine courses of "classical" CMF (cyclophosphamide, methotrexate, and fluorouracil). After a review of all pathology forms, 933 patients (63%) had information on the presence or absence of ECS. ECS was present in 49.5%. The median follow-up was 10 years. RESULTS: In univariate analyses, ECS was associated with worse disease-free survival (DFS) and overall survival (OS). In multivariate analyses adjusting for tumor size, vessel invasion, surgery type, and age group, ECS remained significant (DFS: hazard ratio, 1.61; 95% CI, 1.34 to 1.93; P < .0001; OS: 1.67; 95% CI, 1.34 to 2.08; P < .0001). However, ECS was not significant when the number of positive nodes was added. The locoregional failure rate +/- distant failure (LRF +/- distant failure) within 10 years was estimated at 19% (+/- 2%) without ECS, versus 27% (+/- 2%) with ECS. The difference was statistically significant in univariate analyses, but not after adjusting for the number of positive nodes. No independent effect of ECS on DFS, OS, or LRF could be confirmed within the subgroup of 382 patients with LN1-3+ treated with mastectomy without radiotherapy. CONCLUSION: Our results do not support an independent prognostic value of ECS, nor its use as an indication for irradiation in premenopausal patients with LN1-3+ treated with classical CMF. However, we could not examine whether extensive ECS is of prognostic importance.

Adult↗

PubMed2005

A multistate Markov chain model for longitudinal, categorical quality-of-life data subject to non-ignorable missingness.

Quality-of-life (QOL) is an important outcome in clinical research, particularly in cancer clinical trials. Typically, data are collected longitudinally from patients during treatment and subsequent follow-up. Missing data are a common problem, and missingness may arise in a non-ignorable fashion. In particular, the probability that a patient misses an assessment may depend on the patient's QOL at the time of the scheduled assessment. We propose a Markov chain model for the analysis of categorical outcomes derived from QOL measures. Our model assumes that transitions between QOL states depend on covariates through generalized logit models or proportional odds models. To account for non-ignorable missingness, we incorporate logistic regression models for the conditional probabilities of observing measurements, given their actual values. The model can accommodate time-dependent covariates. Estimation is by maximum likelihood, summing over all possible values of the missing measurements. We describe options for selecting parsimonious models, and we study the finite-sample properties of the estimators by simulation. We apply the techniques to data from a breast cancer clinical trial in which QOL assessments were made longitudinally, and in which missing data frequently arose.

Antineoplastic Agents↗

PubMed2005

Real time spatial cluster detection using interpoint distances among precise patient locations.

BACKGROUND: Public health departments in the United States are beginning to gain timely access to health data, often as soon as one day after a visit to a health care facility. Consequently, new approaches to outbreak surveillance are being developed. When cases cluster geographically, an analysis of their spatial distribution can facilitate outbreak detection. Our method focuses on detecting perturbations in the distribution of pair-wise distances among all patients in a geographical region. Barring outbreaks, this distribution can be quite stable over time. We sought to exemplify the method by measuring its cluster detection performance, and to determine factors affecting sensitivity to spatial clustering among patients presenting to hospital emergency departments with respiratory syndromes. METHODS: The approach was to (1) define a baseline spatial distribution of home addresses for a population of patients visiting an emergency department with respiratory syndromes using historical data; (2) develop a controlled feature set simulation by inserting simulated outbreak data with varied parameters into authentic background noise, thereby creating semisynthetic data; (3) compare the observed with the expected spatial distribution; (4) establish the relative value of different alarm strategies so as to maximize sensitivity for the detection of clustering; and (5) measure factors which have an impact on sensitivity. RESULTS: Overall sensitivity to detect spatial clustering was 62%. This contrasts with an overall alarm rate of less than 5% for the same number of extra visits when the extra visits were not characterized by geographic clustering. Clusters that produced the least number of alarms were those that were small in size (10 extra visits in a week, where visits per week ranged from 120 to 472), diffusely distributed over an area with a 3 km radius, and located close to the hospital (5 km) in a region most densely populated with patients to this hospital. Near perfect alarm rates were found for clusters that varied on the opposite extremes of these parameters (40 extra visits, within a 250 meter radius, 50 km from the hospital). CONCLUSION: Measuring perturbations in the interpoint distance distribution is a sensitive method for detecting spatial clustering. When cases are clustered geographically, there is clearly power to detect clustering when the spatial distribution is represented by the M statistic, even when clusters are small in size. By varying independent parameters of simulated outbreaks, we have demonstrated empirically the limits of detection of different types of outbreaks.

Ambulatory Care↗

PubMed2005

The interpoint distance distribution as a descriptor of point patterns, with an application to spatial disease clustering.

The topic of this paper is the distribution of the distance between two points distributed independently in space. We illustrate the use of this interpoint distance distribution to describe the characteristics of a set of points within some fixed region. The properties of its sample version, and thus the inference about this function, are discussed both in the discrete and in the continuous setting. We illustrate its use in the detection of spatial clustering by application to a well-known leukaemia data set, and report on the results of a simulation experiment designed to study the power characteristics of the methods within that study region and in an artificial homogenous setting.

Cluster Analysis↗

PubMed2004

Patterns of treatment effects in subsets of patients in clinical trials.

We discuss the practice of examining patterns of treatment effects across overlapping patient subpopulations. In particular, we focus on the case in which patient subgroups are defined to contain patients having increasingly larger (or smaller) values of one particular covariate of interest, with the intent of exploring the possible interaction between treatment effect and that covariate. We formalize these subgroup approaches (STEPP: subpopulation treatment effect pattern plots) and implement them when treatment effect is defined as the difference in survival at a fixed time point between two treatment arms. The joint asymptotic distribution of the treatment effect estimates is derived, and used to construct simultaneous confidence bands around the estimates and to test the null hypothesis of no interaction. These methods are illustrated using data from a clinical trial conducted by the International Breast Cancer Study Group, which demonstrates the critical role of estrogen receptor content of the primary breast cancer for selecting appropriate adjuvant therapy. The considerations are also relevant for general subset analysis, since information from the same patients is typically used in the estimation of treatment effects within two or more subgroups of patients defined with respect to different covariates.

Antineoplastic Agents, Phytogenic↗

PubMed2003

Adjuvant chemotherapy followed by goserelin versus either modality alone for premenopausal lymph node-negative breast cancer: a randomized trial.

BACKGROUND: Although chemotherapy and ovarian function suppression are both effective adjuvant therapies for patients with early-stage breast cancer, little is known of the efficacy of their sequential combination. In an International Breast Cancer Study Group (IBCSG) randomized clinical trial (Trial VIII) for pre- and perimenopausal women with lymph node-negative breast cancer, we compared sequential chemotherapy followed by the gonadotropin-releasing hormone agonist goserelin with each modality alone. METHODS: From March 1990 through October 1999, 1063 patients stratified by estrogen receptor (ER) status and radiotherapy plan were randomly assigned to receive goserelin for 24 months (n = 346), six courses of "classical" CMF (cyclophosphamide, methotrexate, 5-fluorouracil) chemotherapy (n = 360), or six courses of classical CMF followed by 18 months of goserelin (CMF --> goserelin; n = 357). A fourth arm (no adjuvant treatment) with 46 patients was discontinued in 1992. Tumors were classified as ER-negative (30%), ER-positive (68%), or ER status unknown (3%). Twenty percent of patients were aged 39 years or younger. The median follow-up was 7 years. The primary outcome was disease-free survival (DFS). RESULTS: Patients with ER-negative tumors achieved better disease-free survival if they received CMF (5-year DFS for CMF = 84%, 95% confidence interval [CI] = 77% to 91%; 5-year DFS for CMF --> goserelin = 88%, 95% CI = 82% to 94%) than if they received goserelin alone (5-year DFS = 73%, 95% CI = 64% to 81%). By contrast, for patients with ER-positive disease, chemotherapy alone and goserelin alone provided similar outcomes (5-year DFS for both treatment groups = 81%, 95% CI = 76% to 87%), whereas sequential therapy (5-year DFS = 86%, 95% CI = 82% to 91%) provided a statistically nonsignificant improvement compared with either modality alone, primarily because of the results among younger women. CONCLUSIONS: Premenopausal women with ER-negative (i.e., endocrine nonresponsive), lymph node-negative breast cancer should receive adjuvant chemotherapy. For patients with ER-positive (i.e., endocrine responsive) disease, the combination of chemotherapy with ovarian function suppression or other endocrine agents, and the use of endocrine therapy alone should be studied.

Adult↗

PubMed2002

High-pressure effects on horse heart metmyoglobin studied by small-angle neutron scattering.

Small-angle neutron scattering experiments were performed on horse azidometmyoglobin (MbN3) at pressures up to 300 MPa. Other spectroscopic techniques have shown that a reorganization of the secondary structure and of the active site occur in this pressure range. The present measurements, performed using various concentrations of MbN3, show that the compactness of the protein is not altered as the value of its radius of gyration remains constant up to 300 MPa. The value of the second virial coefficient of the protein solution indicates that the interactions between the molecules are always strongly repulsive even if their magnitude decreases with increasing pressure. Taking advantage of the pressure-induced contrast variation, these experiments allow the partial specific volume of MbN3 to be determined as a function of pressure. Its value decreases by 5.4% between atmospheric pressure and 300 MPa. In this pressure range the isothermal compressibility of hydrated MbN3 is found to be almost constant. Its value is (1.6 +/- 0.1) 10-4 MPa-1.

Animals↗