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1.
BMC Cancer ; 12: 490, 2012 Oct 22.
Article in English | MEDLINE | ID: mdl-23088658

ABSTRACT

BACKGROUND: Previous studies have found a link between a low DNA repair capacity (DRC) level and increased cancer risk. Our aim was to assess the statistical association of DRC level and breast cancer (BC) using a case-control epidemiological study in a Hispanic community. METHODS: We conducted a comparative observational study to assess the validity of DRC in detecting BC in 824 women throughout Puerto Rico. Over a 6-year period, we compared 285 women newly diagnosed with BC to 539 without BC. DRC levels were measured in lymphocytes by means of a host-cell reactivation assay. We assessed the sensitivity, specificity, and association using the receiver operating characteristic curve analysis. Multiple logistic regression-adjusted odds ratios were estimated with 95% confidence level to measure the strength of the association of DRC and BC after adjusting for all confounders simultaneously. RESULTS: Compared to women without cancer, women with BC showed an average decrease of 60% in their DRC levels (p < 0.001). Validity of the association of DRC as a measure of BC risk showed a sensitivity of 83.2% and specificity of 77.6% (p < 0.0001). CONCLUSIONS: Our results support the usefulness of DRC level as a measure of BC risk. Additional studies in other populations are needed to further verify its usefulness.


Subject(s)
Breast Neoplasms/genetics , DNA Damage/genetics , DNA Repair , Adult , Breast Neoplasms/diagnosis , Breast Neoplasms/epidemiology , Case-Control Studies , Female , Genetic Markers , Humans , Logistic Models , Middle Aged , Puerto Rico/epidemiology , ROC Curve , Reproducibility of Results , Risk Factors , Sensitivity and Specificity , Young Adult
2.
BMC Public Health ; 9: 38, 2009 Jan 26.
Article in English | MEDLINE | ID: mdl-19171059

ABSTRACT

BACKGROUND: Most valid methods to measure treatment adherence require time and resources, and they are not easily applied in highly demanding Primary Health Care Clinics (PHCC). The objective of this study was to determine sensitivity, specificity, predictive values, likelihood ratios, and post-test probabilities of two novel questionnaires as proxy measurements of treatment adherence in Type-2 diabetic patients. METHODS: Two questionnaires were developed by a group of experts to identify the patient's medical prescription knowledge (knowledge) and their attitudes toward treatment adherence (attitudes) as proxy measurements of adherence. The questionnaires were completed by patients receiving care in PHCC pertaining to the Mexican Institute of Social Security in Aguascalientes (Mexico). Pill count was used as gold standard. Participants were selected randomly, and their oral hypoglycemic prescriptions were studied. The main outcome measures for each questionnaire were sensitivity, specificity, predictive values, likelihood ratios, and post-test probabilities, all as an independent questionnaire test and in a serial analysis. RESULTS: Adherence prevalence was 27.0% using pill count. Knowledge questionnaire showed the highest sensitivity (68.1%) and negative predictive value (82.2%), the lowest negative likelihood ratio (0.58) and post-test probability for a negative result (0.16). Serial analysis showed the highest specificity (77.4%) and positive predictive value (40.1%) as well as the highest positive likelihood ratio (1.8) and post-test probability for a positive result (0.39). CONCLUSION: Medical Prescription Knowledge questionnaire showed the best performance as proxy measurement to identify non-adherence in type 2 diabetic patients regarding negative predictive value, negative likelihood ratio, and post-test probability for a negative result. However, Medical Prescription Knowledge questionnaire performance may change in contexts with higher adherence prevalence. Therefore, more research is needed before using this method in other contexts.


Subject(s)
Diabetes Mellitus, Type 2/therapy , Health Knowledge, Attitudes, Practice , Patient Compliance/statistics & numerical data , Surveys and Questionnaires , Age Factors , Aged , Cohort Studies , Diabetes Mellitus, Type 2/diagnosis , Diet, Diabetic , Female , Follow-Up Studies , Humans , Hypoglycemic Agents/administration & dosage , Life Style , Likelihood Functions , Male , Mexico , Middle Aged , Predictive Value of Tests , Quality of Life , Risk Factors , Sensitivity and Specificity , Sex Factors , Socioeconomic Factors , Treatment Outcome
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