| dc.description.abstract | Breast cancer remains the most commonly diagnosed cancer among women, affecting
34 women per every 100,000. This has led to high number of fatalities annually,
which need to be mitigated. The main interest among many cancer survivors and their
families is establishing other conventional therapies they can engage in to improve
their prognosis and survival. Among some of the key therapies is the interest in
working on mindfulness-based stress (MBS) that patients undergo after diagnosis as
complementary and alternate measures. Regardless of this, there is little that is known
about the effects of MBS factors on breast cancer survival. Management of breast
cancer can be enhanced through modelling the effects of MBS on breast cancer
survival rate. However, there is limited information on accuracy of existing models.
This study focused on developing a model to predict the effect MBS factors have on
breast cancer survival rate among women in Meru and Nyeri Counties. Both Primary
data and Secondary data were used. Primary data was obtained using a structured
questionnaire from the breast cancer survivors and the medical practioners while
secondary data was obtained from records at Meru teaching and referral hospital and
Nyeri level five hospital on the MBS variables (cost burden of treatment, stress on
diagnosis, prolonged time taken to access treatment, poor diet, alcohol use, physical
activity and lack of awareness) among breast cancer patients for the period 2012 to
2017. Mixed method research design was used in the study. Both quantitative and
qualitative data used in the study was analysed using R software. Cox proportional
hazard model was used in establishing the survival rates, with the breast cancer
survival rate being dependent variable while MBS factors were the independent
variables. Kaplain-Meier estimators were used in determining the varying effects
which the MBS factors have on survival rate. Log-rank test was used to perform
comparisons of survival curves using hypothesis tests on the patients‘ survival rate
considering age. The likelihood ratio test showed that MBS factors are significant in
predicting hazard rates ( = 66.7, p = 0.0000119). Treatment period was highly
statistically significant (p = 0.00014) as compared to other covariates. Lack of
awareness (p = 0.0010124), ease of coping with stress (p = 0.000514) and observing
the right diet (p = 0.04092) were also found to significantly affect survival rate.
Access of treatment immediately after diagnosis, availing the right information to the
patients, helping patients to cope easily with stress and observing the right diet were
found to be the best estimators in increasing breast cancer survival rate. The study
therefore recommends use of the model in predicting breast cancer survival rates
which can greatly improve breast cancer prognosis. | en_US |
