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At least 1,315 records · Page 73Linked to original sources
PubMed2005

Detection of oxaliplatin-induced DNA crosslinks in vitro and in cancer patients using the alkaline comet assay.

Oxaliplatin is frequently used in the therapy of cancer. In DNA, oxaliplatin induces, like cisplatin, the formation of crosslinks, which are commonly accepted as being responsible for the cytotoxicity of platinum agents. The detection of oxaliplatin-induced DNA crosslink formation and repair could be a good measure of assessing how a patient is responding to the agent. In this study, we used a validated modification of the alkaline comet assay for detecting the presence of these crosslinks in vitro and in cancer patients. The H460 tumour cell line was treated in vitro with a range of oxaliplatin and cisplatin doses, and the subsequent crosslink formation and repair compared between the two agents. In addition, lymphocytes from cancer patients undergoing oxaliplatin-based chemotherapy were assayed for the formation and repair of oxaliplatin-induced crosslinks. A dose-response was observed in the in vitro samples, with cisplatin producing more crosslinks than oxaliplatin at equimolar concentrations and lesions induced by both agents showing different repair efficiencies. Furthermore, evidence of crosslink formation and repair was observed in the peripheral blood lymphocytes of all cancer patients studied, along with the detection of interindividual variability in crosslink formation and repair efficiencies. To the best of our knowledge, this is the first time that oxaliplatin DNA crosslinks have been detected either in vitro or in patient samples using the alkaline comet assay. Due to its sensitivity, rapidity, small cell sample and low cost, the alkaline comet assay is a good method for the detection of oxaliplatin-induced crosslinks and their subsequent repair and, in future clinical studies, could prove to be a valuable tool in assessing/predicting a patient's response to chemotherapy.

Aged↗
PubMed2004

Cancer death statistics: analogy between epidemiology and critical systems in physics.

The determination of risk factors in carcinogenesis is said to be an essential step towards the understanding of this disease. Most mathematical models describing the evolution of mortality figures use the concept of death probability (or "force of mortality" or "hazard of death"). When summarizing the death statistics through this unique parameter, one implicitly makes the assumption that the death events are independent from one individual to another. In this paper, we show that this hypothesis has profound consequences as it implies a "gaussian" behavior of the death statistics fluctuations. In order to verify the validity of this assumption, French cancer death statistics between the years 1978-1996 are examined. Their fluctuations, for every age bracket, are computed and then compared to the expected gaussian fluctuations that should emerge from a model of death probability. We show that the observed fluctuations are in close agreement with a gaussian model up to 35-40 years. After 40 years, the fluctuations are much higher and cannot be explained by a model where every individual would have a given "probability of death". These observations may produce a new insight into old-age cancer mortality. It suggests that there could exist a major difference between cancers in young or older organisms: cancer developed in young organisms are the consequence of a specific attack against an organ (essentially originated from a single cause, like a virus or a genetic deficiency). On the other hand, older organism are closer to a "critical state" and, as such, the outcome of a cancer in a given organ could be the consequence of a chain of "malfunctions" (analogous to an avalanche in physical systems) in the entire organism.

Adolescent↗
PubMed2006

Estimating and modeling the cure fraction in population-based cancer survival analysis.

In population-based cancer studies, cure is said to occur when the mortality (hazard) rate in the diseased group of individuals returns to the same level as that expected in the general population. The cure fraction (the proportion of patients cured of disease) is of interest to patients and is a useful measure to monitor trends in survival of curable disease. There are 2 main types of cure fraction model, the mixture cure fraction model and the non-mixture cure fraction model, with most previous work concentrating on the mixture cure fraction model. In this paper, we extend the parametric non-mixture cure fraction model to incorporate background mortality, thus providing estimates of the cure fraction in population-based cancer studies. We compare the estimates of relative survival and the cure fraction between the 2 types of model and also investigate the importance of modeling the ancillary parameters in the selected parametric distribution for both types of model.

Aged↗
PubMed1995

Trends in survival after childhood cancer in Denmark, 1943-87: a population-based study.

Survival from cancer in childhood and adolescence was studied in a population-based series of 8312 cases in children aged 0-19 years notified to the Danish Cancer Registry during 1943-87. During the first period (1943-72), 5-year survival rates from all malignant neoplasms increased from 23% (1943-52) to 33% (1963-72). The greatest improvement was seen during the period 1973-87 when 5-year survival rates reached 64% (1983-87). Between 1973-77 and 1983-87, 5-year survival rates increased from 32% to 62% for leukaemia, from 40% to 70% for acute lymphoblastic leukaemia, from 35% to 54% for non-Hodgkin's lymphoma, from 50% to 66% for central nervous system neoplasms and from 25% to 49% for bone tumours. An improvement in 5-year survival rates from Wilms' tumour was seen between 1960 (19%) and 1980 (81%). Up to 1972, the 5-year survival rate from germ-cell neoplasms was approximately 40%; among patients diagnosed in 1983-87, 76% survived for 5-years. Annual lethality decreased by 2.5% for all malignant neoplasms in 1943-72 and by 4.4% in 1972-87. Lethality was similar for boys and girls during the period 1943-72, but was significantly lower for girls subsequently. A marked effect of age at diagnosis was seen in the early registration period, where lethality rate for the age group 0-9 years was substantially higher compared with that in the age group 10-19 years. This inequality persisted only for children less than 2 years of age at the time of diagnosis in the later period.

Adolescent↗
PubMed2005

An investigation into the psychometric properties of the Hospital Anxiety and Depression Scale in patients with breast cancer.

BACKGROUND: To determine the psychometric properties of the Hospital Anxiety and Depression Scale (HADS) in patients with breast cancer and determine the suitability of the instrument for use with this clinical group. METHODS: A cross-sectional design was used. The study used a pooled data set from three breast cancer clinical groups. The dependent variables were HADS anxiety and depression sub-scale scores. Exploratory and confirmatory factor analyses were conducted on the HADS to determine its psychometric properties in 110 patients with breast cancer. Seven models were tested to determine model fit to the data. RESULTS: Both factor analysis methods indicated that three-factor models provided a better fit to the data compared to two-factor (anxiety and depression) models for breast cancer patients. Clark and Watson's three factor tripartite and three factor hierarchical models provided the best fit. CONCLUSION: The underlying factor structure of the HADS in breast cancer patients comprises three distinct, but correlated factors, negative affectivity, autonomic anxiety and anhedonic depression. The clinical utility of the HADS in screening for anxiety and depression in breast cancer patients may be enhanced by using a modified scoring procedure based on a three-factor model of psychological distress. This proposed alternate scoring method involving regressing autonomic anxiety and anhedonic depression factors onto the third factor (negative affectivity) requires further investigation in order to establish its efficacy.

Adult↗
PubMed2004

Simulation-based parameter estimation for complex models: a breast cancer natural history modelling illustration.

Simulation-based parameter estimation offers a powerful means of estimating parameters in complex stochastic models. We illustrate the application of these ideas in the setting of a natural history model for breast cancer. Our model assumes that the tumor growth process follows a geometric Brownian motion; parameters are estimated from the SEER registry. Our discussion focuses on the use of simulation for computing the maximum likelihood estimator for this class of models. The analysis shows that simulation provides a straightforward means of computing such estimators for models of substantial complexity.

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