Pre-treatment hematological parameters as a cost effective predictive marker for response to concurrent chemo radiation in locally advanced cervical cancer.

INTRODUCTION: Locally advanced cervical cancer is still a major cause of mortality in developing countries. Recently, personalized medicine has changed the treatment paradigm for many solid cancers but no robust biomarkers has yet been validated for predicting response to chemo radiation in cervical cancer patients. AIM: To assess the role of hematological parameters as a cost-effective predictive marker of response to concurrent chemo radiation in cervical cancer patients. MATERIALS AND METHOD: This is a retrospective analysis of 90 cervical cancer patients treated with concurrent chemo radiation in a tertiary cancer center. Clinical details of the patients were extracted from the case records. For end point evaluation, the pre-treatment levels of hemoglobin, neutrophil, lymphocyte, platelet, platelet lymphocyte ratio (PLR) and neutrophil lymphocyte ratio (NLR) were compared and statistically analyzed between responders and non-responders. The optimal cutoff values of hematological parameters were estimated by the receiver operating characteristics (ROC) curve. RESULT: Out of 90 patients, 60 (66.66%) were complete responders and remaining 30 (33.33%) were non-responders. The mean value of platelet, NLR, and PLR was significantly higher in the non-responder group. ROC curve analysis showed the optimal cut-off value of pre-treatment Hb, PLT, NLR and PLR to be 11 gm/dl, 3, 177 × 109/L, and 70 respectively. CONCLUSION: Our study suggests that simple hematological markers like NLR, PLT count and PLR could be used as a cost effective pretreatment predictive marker for response to chemo radiation in cervical cancer patients.

Development of a Clinical Prediction Model for In-hospital Mortality from the South African Cohort of the African Surgical Outcomes Study.

BACKGROUND: Data on the factors that influence mortality after surgery in South Africa are scarce, and neither these data nor data on risk-adjusted in-hospital mortality after surgery are routinely collected. Predictors related to the context or setting of surgical care delivery may also provide insight into variation in practice. Variation must be addressed when planning for improvement of risk-adjusted outcomes. Our objective was to identify the factors predicting in-hospital mortality after surgery in South Africa from available data. METHODS: A multivariable logistic regression model was developed to identify predictors of 30-day in-hospital mortality in surgical patients in South Africa. Data from the South African contribution to the African Surgical Outcomes Study were used and included 3800 cases from 51 hospitals. A forward stepwise regression technique was then employed to select for possible predictors prior to model specification. Model performance was evaluated by assessing calibration and discrimination. The South African Surgical Outcomes Study cohort was used to validate the model. RESULTS: Variables found to predict 30-day in-hospital mortality were age, American Society of Anesthesiologists Physical Status category, urgent or emergent surgery, major surgery, and gastrointestinal-, head and neck-, thoracic- and neurosurgery. The area under the receiver operating curve or c-statistic was 0.859 (95% confidence interval: 0.827-0.892) for the full model. Calibration, as assessed using a calibration plot, was acceptable. Performance was similar in the validation cohort as compared to the derivation cohort. CONCLUSION: The prediction model did not include factors that can explain how the context of care influences post-operative mortality in South Africa. It does, however, provide a basis for reporting risk-adjusted perioperative mortality rate in the future, and identifies the types of surgery to be prioritised in quality improvement projects at a local or national level.

Factors associated with low birth weight in Nepal using multiple imputation.

BACKGROUND: Survey data from low income countries on birth weight usually pose a persistent problem. The studies conducted on birth weight have acknowledged missing data on birth weight, but they are not included in the analysis. Furthermore, other missing data presented on determinants of birth weight are not addressed. Thus, this study tries to identify determinants that are associated with low birth weight (LBW) using multiple imputation to handle missing data on birth weight and its determinants. METHODS: The child dataset from Nepal Demographic and Health Survey (NDHS), 2011 was utilized in this study. A total of 5,240 children were born between 2006 and 2011, out of which 87% had at least one measured variable missing and 21% had no recorded birth weight. All the analyses were carried out in R version 3.1.3. Transform-then impute method was applied to check for interaction between explanatory variables and imputed missing data. Survey package was applied to each imputed dataset to account for survey design and sampling method. Survey logistic regression was applied to identify the determinants associated with LBW. RESULTS: The prevalence of LBW was 15.4% after imputation. Women with the highest autonomy on their own health compared to those with health decisions involving husband or others (adjusted odds ratio (OR) 1.87, 95% confidence interval (95% CI) = 1.31, 2.67), and husband and women together (adjusted OR 1.57, 95% CI = 1.05, 2.35) were less likely to give birth to LBW infants. Mothers using highly polluting cooking fuels (adjusted OR 1.49, 95% CI = 1.03, 2.22) were more likely to give birth to LBW infants than mothers using non-polluting cooking fuels. CONCLUSION: The findings of this study suggested that obtaining the prevalence of LBW from only the sample of measured birth weight and ignoring missing data results in underestimation.

Assessment of prophylactic effect of Senna auriculata (L.) Roxb. leaves on alcohol-induced pancreatitis in rat model.

Aqueous leaf extract of Senna auriculata (L.) Roxb. syn. Cassia auriculata (SLEx) is known to possess potential antidiabetic and antioxidant properties. Based on the known correlation between exocrine pancreatic function and endocrine secretary capacity, here, we studied the prophylactic effect of the SLEx on alcohol induced pancreatitis in rats. To induce chronic pancreatitis, the rats were fed with unsaturated fat i.e. corn oil (2.5 mL/kg) along with high dose of ethanol (10.2 g/kg) for 4 wk, and was increased 0.6 g/kg after every 2 days for 1 wk and then 0.6 g/kg after every 4 days for a period of 4 wk. SLEx was orally administered to rats at dose of 400 mg/kg/day for 4 wk. At the end of 4th wk, pancreatic enzymes i.e., α-amylase, lipase, serum and pancreatic MDA levels were estimated. Pancreatic histopathological studies were also performed. The SLEx significantly reduced the serum levels of α-amylase and lipase along with significant suppression in serum and pancreatic tissue lipid peroxidation. Histomorphological studies did not show any fatty vacoules in acinar cells of SLEx-treated rats. However, vacoulation was seen in acini of pathogenic control rats. With the results, we conclude that Senna auriculata aqueous leaf extract has potential to reduce the ethanol-induced pathogenecity, and it possesses prophylactic effect on alcohol-induced pancreatitis. However, a long term trial is needed to ascertain its therapeutic potential for pancreatitis.

Assessment of predictive markers of response to neoadjuvant chemotherapy in breast cancer.

OBJECTIVE: To identify the predictive markers associated with chemotherapy sensitivity, especially those producing pathological complete response (pCR) following neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer. METHODS: Core needle biopsy of 50 locally advanced breast cancer patients was analysed for histopathology, grade, oestrogen receptor, progesterone receptor, HER2, Ki-67, p53, Bcl-2, and BAX before starting NACT. This was correlated with response to NACT using Response Evaluation Criteria in Solid Tumours criteria. RESULTS: The mean tumour reduction rate per chemotherapy cycle was significantly higher in BAX-positive (p = 0.01) and Bcl-2-negative (p = 0.04) tumours. BAX expression significantly (p = 0.043) correlated with a response of an at least 30% reduction in tumour size post-NACT on multivariate analysis. A significant relationship was seen between loss of Bcl-2 expression and pCR on univariate (p = 0.048) analysis. Overall, all of the above 12 parameters had 30.4% and 28.5% success in predicting clinical complete response and pCR, respectively, by the Cox and Snell formula. CONCLUSION: Of all parameters examined, only the apoptosis-related genes (Bcl-2 and BAX) seemed to exert some influence on the response to NACT, and neither by itself was sufficient to predict pCR; however, 50 patients is not sufficient to simultaneously analyse several predictive markers.