Survival analysis of female dogs with mammary tumors after mastectomy: epidemiological, clinical and morphological aspects

Abstract: Mammary gland tumors are the most common type of tumors in bitches but research on survival time after diagnosis is scarce. The purpose of this study was to investigate the relationship between survival time after mastectomy and a number of clinical and morphological variables. Data was collected retrospectively on bitches with mammary tumors seen at the Small Animal Surgery Clinic Service at the University of Brasília. All subjects had undergone mastectomy. Survival analysis was conducted using Cox's proportional hazard method. Of the 139 subjects analyzed, 68 died and 71 survived until the end of the study (64 months). Mean age was 11.76 years (SD=2.71), 53.84% were small dogs. 76.92% of the tumors were malignant, and 65.73% had both thoracic and inguinal glands affected. Survival time in months was associated with age (hazard rate ratios [HRR] =1.23, p-value =1.4x10-4), animal size (HRR between giant and small animals =2.61, p-value =0.02), nodule size (HRR =1.09, p-value =0.03), histological type (HRR between solid carcinoma and carcinoma in a mixed tumor =2.40, p-value =0.02), time between diagnosis and surgery (TDS, with HRR =1.21, p-value =2.7x10-15), and the interaction TDS*follow-up time (HRR =0.98, p-value =1.6x10-11). The present study is one of the few on the subject matter. Several important covariates were evaluated and age, animal size, nodule size, histological type, TDS and TDS*follow up time were identified as significantly associated to survival time.

Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

Evaluation of a 1-h 75-g oral glucose tolerance test in the diagnosis of gestational diabetes

In order to evaluate the performance of a 1-h 75-g oral glucose tolerance test (OGTT) for the diagnosis of gestational diabetes mellitus (GDM), a cohort of 4998 women, 20 years or older, without previous diabetes being treated in prenatal care clinics in Brazil answered a questionnaire and performed a 75-g OGTT including fasting, 1-h and 2-h glucose measurements between their 24th and 28th gestational weeks. Pregnancy outcomes were transcribed from medical registries. GDM was defined according to WHO criteria (fasting: ≥126 mg/dL; 2-h value: ≥140 mg/dL) and macrosomia as a birth weight equal to or higher than 4000 g. Areas under the receiver operator characteristic curve (AUC) were compared and diagnostic properties of various cut-off points were evaluated. The AUCs for the prediction of macrosomia were 0.606 (0.572-0.637) for the 1-h and 0.589 (0.557-0.622) for the 2-h plasma glucose test. Similar predictability was demonstrable regarding combined adverse outcomes: 0.582 (0.559-0.604) for the 1-h test and 0.572 (0.549-0.595) for the 2-h test. When the 1-h glucose test was evaluated against a diagnosis of GDM defined by the 2-h glucose test, the AUC was 0.903 (0.886-0.919). The cut-off point that maximized sensitivity (83%) and specificity (83%) was 141 mg/dL, identifying 21% of the women as positive. A cut-off point of 160 mg/dL, with lower sensitivity (62%), had higher specificity (94%), labeling 8.6% as positive. Detection of GDM can be done with a 1-h 75-g OGTT: the value of 160 mg/dL has the same diagnostic performance as the conventional 2-h value (140 mg/dL). The simplification of the test may improve coverage and timing of the diagnosis of GDM.