OBJECTIVES: To evaluate the economic burden of treating cancer patients.
METHOD: Descriptive cross-sectional cost of illness study in the leading teaching and referral hospital in Kenya, with data collected from the hospital files of sampled adult patients for treatment during 2016.
RESULTS: In total, 412 patient files were reviewed, of which 63.4% (n = 261) were female and 36.6% (n = 151) male. The cost of cancer care is highly dependent on the modality. Most reviewed patients had surgery, chemotherapy and palliative care. The cost of cancer therapy varied with the type of cancer. Patients on chemotherapy alone cost an average of KES 138,207 (USD 1364.3); while those treated with surgery cost an average of KES 128,207 (1265.6), and those on radiotherapy KES 119,036 (1175.1). Some patients had a combination of all three, costing, on average, KES 333,462 (3291.8) per patient during the year.
CONCLUSION: The cost of cancer treatment in Kenya depends on the type of cancer, the modality, cost of medicines and the type of inpatient admission. The greatest contributors are currently the cost of medicines and inpatient admissions. This pilot study can inform future initiatives among the government as well as private and public insurance companies to increase available resources, and better allocate available resources, to more effectively treat patients with cancer in Kenya. The authors will be monitoring developments and conducting further research.
MATERIALS AND METHODS: A cross-sectional study involving bereaved individuals in Palliative Care Unit Hospital Selayang. Participants (n=175) were recruited through telephone, and a validated tool Prolonged Grief Disorder Scale (PG-13) was asked to identify PGD. Further data collected were concomitant stressors in life and support system in the bereaved individual.
RESULTS: Prevalence of PGD was 2.9% (n=5), and subthreshold PGD was 4% (n=7). A model of multiple logistic regression calculated most of the traditional risk factors were not significant except having an increased responsibility as a single parent after passing of a spouse or loved one, had 10 times increased odds of PGD (Odds Ratios: 10.93; 95% Confidence Interval: 2.937, 40.661). Otherwise, immediate family support (80%), religion (60%) and community (40%) support were the top three coping mechanisms of our PGD cohort, although they were not significant in a multiple logistic regression model.
CONCLUSION: Our PGD percentage may not be as high as those of other countries, but nonetheless they exist and their needs are just as important. The authors hope that this paper may create an awareness among the healthcare clinicians about PGD in our society, for a greater access of service to understand them and better public awareness.
METHODS: This was a cross-sectional, single-centre study conducted via questionnaire. Patients aged 18 years old and above, who were diagnosed with non-curable pulmonary hypertension were recruited and given the assessment tool - perceptions of palliative care instrument electronically. The severity of pulmonary hypertension was measured using WHO class, N-terminal pro B-type natriuretic peptide and the 6-minute walking test distance.
RESULTS: A total of 84 patients [mean age: 35 ±11 years, female: 83.3%, median N-terminal pro B-type natriuretic peptide: 491 pg/ml (interquartile range: 155,1317.8), median 6-minute walking test distance: 420m (interquartile range: 368.5, 480m)] completed the questionnaires. Patients with a higher WHO functional class and negative feelings (r = 0.333, p = 0.004), and cognitive reaction to palliative care: hopeless (r = 0.340, p = 0.003), supported (r = 0.258, p = 0.028), disrupted (r = 0.262, p = 0.025), and perception of burden (r = 0.239, p = 0.041) are more receptive to palliative care. WHO class, N-terminal pro B-type natriuretic peptide, and 6-minute walking test distance were not associated with higher readiness for palliative care. In logistic regression analyses, patients with positive feelings (β = 2.240, p = < 0.05), and practical needs (β = 1.346, p = < 0.05), were more receptive to palliative care.
CONCLUSIONS: Disease severity did not directly influence patients' readiness for palliative care. Patients with a positive outlook were more receptive to palliative care.
METHODS: Data from 585 eligible patients who received palliative radiotherapy between January 2012 and December 2014 were analysed. Median overall survival was calculated from the commencement of first fraction of the last course of radiotherapy to date of death or when censored. 30-DM was calculated as the proportion of patients who died within 30 days from treatment start date. Kaplan-Meier survival analysis was used to estimate survival. Chi-square test and logistic regression was used to assess the impact of potential prognostic factors on median survival and 30-DM.
RESULTS: The most common diagnoses were lung and breast cancers and most common irradiated sites were bone and brain. Median survival and 30-DM were 97 days and 22.7% respectively. Primary cancer, age, treatment course, performance status, systemic treatment post radiotherapy and intended radiotherapy treatment completed had an impact on median survival whereas mainly the latter three factors had an impact on 30-DM.
CONCLUSION: Median survival and factors affecting both survival and 30-DM in our study are comparable to others. However, a 30-DM rate of 22.7% is significantly higher compared to the literature. We need to better select patients who will benefit from palliative radiotherapy in our centre.