Effect of phyto additives and Saccharomyces cerevisiae on rumen ferementation and microbial profile in buffaloes

To study the effect of plants containing plant secondary metabolites (PSM) and Saccharomyces cerevisiae on rumen ferementation and microbial profile, four fistulated adult buffaloes were fed in 4×4 Latin square design. The four groups were, control, without additive; T1, mixture of harad seed pulp and garlic bulb (2% of DMI); T2, S. cerevisiae (350g feremented feed containing S. cerevisiae 106 /g); T3, mixture of harad seed pulp, garlic bulb and S. cerevisiae. All the animals were fed on a basal diet consisting of wheat straw and concentrate mixture in 50:50 ratio. Daily DM intake was similar in all the four groups. Feeding of any of the dietary treatments did not affect rumen fluid pH, concentration of ammonia N and lactic acid. The total volatile fatty acids and its fractions except butyrate were also not influenced by supplementation of any of the additives. The activities of ruminal enzymes viz. carboxymethylcellulase, xylanase, avicelase and acetyl esterase were similar in all the four groups. The rumen microbial density of total bacteria, Ruminococcus flavefaciences, R. albus, methanogens and fungi were not changed whereas Fibrobacter succinogenes and protozoa populations were significantly reduced in T1 but were at par of control by inclusion of yeast in the diet. It is concluded that mixture of harad and garlic alone or in combination with yeast culture did not influence rumen fermentation however microbial profile (F. succinogenes and protozoa) was improved by feeding yeast as additive. The additives tested seem to have potential to alter rumen microbial ecology and can further be explored for its efficacy in improving the performance of the animals

Light smoking at base-line predicts a higher mortality risk to women than to men; evidence from a cohort with long follow-up

BACKGROUND: There is conflicting evidence as to whether smoking is more harmful to women than to men. The UK Cotton Workers’ Cohort was recruited in the 1960s and contained a high proportion of men and women smokers who were well matched in terms of age, job and length of time in job. The cohort has been followed up for 42 years. METHODS: Mortality in the cohort was analysed using an individual relative survival method and Cox regression. Whether smoking, ascertained at baseline in the 1960s, was more hazardous to women than to men was examined by estimating the relative risk ratio women to men, smokers to never smoked, for light (1–14), medium (15–24), heavy (25+ cigarettes per day) and former smoking. RESULTS: For all-cause mortality relative risk ratios were 1.35 for light smoking at baseline (95% CI 1.07-1.70), 1.15 for medium smoking (95% CI 0.89-1.49) and 1.00 for heavy smoking (95% CI 0.63-1.61). Relative risk ratios for light smoking at baseline for circulatory system disease was 1.42 (95% CI 1.01 to 1.98) and for respiratory disease was 1.89 (95% CI 0.99 to 3.63). Heights of participants provided no explanation for the gender difference. CONCLUSIONS: Light smoking at baseline was shown to be significantly more hazardous to women than to men but the effect decreased as consumption increased indicating a dose response relationship. Heavy smoking was equally hazardous to both genders. This result may help explain the conflicting evidence seen elsewhere. However gender differences in smoking cessation may provide an alternative explanation

The impact of life tables adjusted for smoking on the socio-economic difference in net survival for laryngeal and lung cancer.

BACKGROUND: Net survival is a key measure in cancer control, but estimates for cancers that are strongly associated with smoking may be biased. General population life tables represent background mortality in net survival, but may not adequately reflect the higher mortality experienced by smokers. METHODS: Life tables adjusted for smoking were developed, and their impact on net survival and inequalities in net survival for laryngeal and lung cancers was examined. RESULTS: The 5-year net survival estimated with smoking-adjusted life tables was consistently higher than the survival estimated with unadjusted life tables: 7% higher for laryngeal cancer and 1.5% higher for lung cancer. The impact of using smoking-adjusted life tables was more pronounced in affluent patients; the deprivation gap in 5-year net survival for laryngeal cancer widened by 3%, from 11% to 14%. CONCLUSIONS: Using smoking-adjusted life tables to estimate net survival has only a small impact on the deprivation gap in survival, even when inequalities are substantial. Adjusting for the higher, smoking-related background mortality did increase the estimates of net survival for all deprivation groups, and may be more important when measuring the public health impact of differences or changes in survival, such as avoidable deaths or crude probabilities of death

Deriving stage at diagnosis from multiple population-based sources: colorectal and lung cancer in England.

BACKGROUND: Stage at diagnosis is a strong predictor of cancer survival. Differences in stage distributions and stage-specific management help explain geographic differences in cancer outcomes. Stage information is thus essential to improve policies for cancer control. Despite recent progress, stage information is often incomplete. Data collection methods and definition of stage categories are rarely reported. These inconsistencies may result in assigning conflicting stage for single tumours and confound the interpretation of international comparisons and temporal trends of stage-specific cancer outcomes. We propose an algorithm that uses multiple routine, population-based data sources to obtain the most complete and reliable stage information possible. METHODS: Our hierarchical approach derives a single stage category per tumour prioritising information deemed of best quality from multiple data sets and various individual components of tumour stage. It incorporates rules from the Union for International Cancer Control TNM classification of malignant tumours. The algorithm is illustrated for colorectal and lung cancer in England. We linked the cancer-specific Clinical Audit data (collected from clinical multi-disciplinary teams) to national cancer registry data. We prioritise stage variables from the Clinical Audit and added information from the registry when needed. We compared stage distribution and stage-specific net survival using two sets of definitions of summary stage with contrasting levels of assumptions for dealing with missing individual TNM components. This exercise extends a previous algorithm we developed for international comparisons of stage-specific survival. RESULTS: Between 2008 and 2012, 163 915 primary colorectal cancer cases and 168 158 primary lung cancer cases were diagnosed in adults in England. Using the most restrictive definition of summary stage (valid information on all individual TNM components), colorectal cancer stage completeness was 56.6% (from 33.8% in 2008 to 85.2% in 2012). Lung cancer stage completeness was 76.6% (from 57.3% in 2008 to 91.4% in 2012). Stage distribution differed between strategies to define summary stage. Stage-specific survival was consistent with published reports. CONCLUSIONS: We offer a robust strategy to harmonise the derivation of stage that can be adapted for other cancers and data sources in different countries. The general approach of prioritising good-quality information, reporting sources of individual TNM variables, and reporting of assumptions for dealing with missing data is applicable to any population-based cancer research using stage. Moreover, our research highlights the need for further transparency in the way stage categories are defined and reported, acknowledging the limitations, and potential discrepancies of using readily available stage variables

Validation of prediction models in the presence of competing risks: a guide through modern methods

Thorough validation is pivotal for any prediction model before it can be advocated for use in medical  practice. For time-to-event outcomes such as breast cancer recurrence, death from other causes is a competing risk. Model performance measures must account for such competing events. In this article, we present a comprehensive yet accessible overview of performance measures for this competing eventsetting, including the calculation and interpretation of statistical measures for calibration, discrimination, overall prediction error, and clinical usefulness by decision curve analysis. All methods are illustrated for patients with breast cancer, with publicly available data and R code.Development and application of statistical models for medical scientific researc

Is Cancer survival associated with cancer symptom awareness and barriers to seeking medical help in England? An ecological study

Abstract BACKGROUND: Campaigns aimed at raising cancer awareness and encouraging early presentation have been implemented in England. However, little is known about whether people with low cancer awareness and increased barriers to seeking medical help have worse cancer survival, and whether there is a geographical variation in cancer awareness and barriers in England. METHODS: From population-based surveys (n=35?308), using the Cancer Research UK Cancer Awareness Measure, we calculated the age- and sex-standardised symptom awareness and barriers scores for 52 primary care trusts (PCTs). These measures were evaluated in relation to the sex-, age-, and type of cancer-standardised cancer survival index of the corresponding PCT, from the National Cancer Registry, using linear regression. Breast, lung, and bowel cancer survival were analysed separately. RESULTS: Cancer symptom awareness and barriers scores varied greatly between geographical regions in England, with the worst scores observed in socioeconomically deprived parts of East London. Low cancer awareness score was associated with poor cancer survival at PCT level (estimated slope=1.56, 95% CI: 0.56; 2.57). The barriers score was not associated with overall cancer survival, but it was associated with breast cancer survival (estimated slope=-0.66, 95% CI: -1.20; -0.11). Specific barriers, such as embarrassment and difficulties in arranging transport to the doctor's surgery, were associated with worse breast cancer survival. CONCLUSIONS: Cancer symptom awareness and cancer survival are associated. Campaigns should focus on improving awareness about cancer symptoms, especially in socioeconomically deprived areas. Efforts should be made to alleviate barriers to seeking medical help in women with symptoms of breast cancer.British Journal of Cancer advance online publication 18 August 2016; doi:10.1038/bjc.2016.246 www.bjcancer.com

Accuracy of cause of death data routinely recorded in a population-based cancer registry: impact on cause-specific survival and validation using the Geneva Cancer Registry.

BACKGROUND: Information on the underlying cause of death of cancer patients is of interest because it can be used to estimate net survival. The population-based Geneva Cancer Registry is unique because registrars are able to review the official cause of death. This study aims to describe the difference between the official and revised cause-of-death variables and the impact on cancer survival estimates. METHODS: The recording process for each cause of death variable is summarised. We describe the differences between the two cause-of-death variables for the 5,065 deceased patients out of the 10,534 women diagnosed with breast cancer between 1970 and 2009. The Kappa statistic and logistic regression are applied to evaluate the degree of concordance. The impact of discordance on cause-specific survival is examined using the Kaplan Meier method. RESULTS: The overall agreement between the two variables was high. However, several subgroups presented a lower concordance, suggesting differences in calendar time and less attention given to older patients and more advanced diseases. Similarly, the impact of discordance on cause-specific survival was small on overall survival but larger for several subgroups. CONCLUSION: Estimation of cancer-specific survival could therefore be prone to bias when using the official cause of death. Breast cancer is not the more lethal cancer and our results can certainly not be generalised to more lethal tumours

Trends in incidence, mortality and survival in women with breast cancer from 1985 to 2012 in Granada, Spain: a population-based study

The incidence of breast cancer has increased since the 1970s. Despite favorable trends in prognosis, the role of changes in clinical practice and the introduction of screening remain controversial. We examined breast cancer trends to shed light on their determinants Overall, age-adjusted (European Standard Population) incidence rates increased from 48.0 cases × 100,000 women in 1985–1989 to 83.4 in 2008–2012, with an annual percentage change (APC) of 2.5% (95%CI, 2.1–2.9) for 1985–2012. The greatest increase was in women younger than 40 years (APC 3.5, 95%CI, 2.4–4.8). For 2000–2012 the incidence trend increased only for stage I tumors (APC 3.8, 95%CI, 1.9–5.8). Overall age-adjusted breast cancer mortality decreased (APC − 1, 95%CI, − 1.4 – − 0.5), as did mortality in the 50–69 year age group (APC − 1.3, 95%CI, − 2.2 – − 0.4). Age-standardized net survival increased from 67.5% at 5 years in 1985–1989 to 83.7% in 2010–2012. All age groups younger than 70 years showed a similar evolution. Five-year net survival rates were 96.6% for patients with tumors diagnosed in stage I, 88.2% for stage II, 62.5% for stage III and 23.3% for stage IV. Breast cancer incidence is increasing – a reflection of the evolution of risk factors and increasing diagnostic pressure. After screening was introduced, the incidence of stage I tumors increased, with no decrease in the incidence of more advanced stages. Reductions were seen for overall mortality and mortality in the 50–69 year age group, but no changes were found after screening implementation. Survival trends have evolved favorably except for the 70–84 year age group and for metastatic tumors.This study was supported by a grant from the Acción Estratégica en Salud plan for the High Resolution Project on Prognosis and Care of Cancer Patients (No. AC14/00036) awarded by the Spanish Ministry of Economy and Competitiveness and co-funded by the European Regional Development Fund (ERDF)