METHODS: ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs.
ETHICS AND DISSEMINATION: The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.
METHODS: Patients diagnosed with invasive breast cancer (BC) from 2005 to 2013 at our tertiary institution were included and divided according to race and subtypes. Demographic and clinical information of non-metastatic TNBC patients were analyzed. Log-rank test, univariate and multivariate Cox proportional hazard regression models were used to find associated risk factors related with overall survival (OS) and disease-free survival (DFS).
RESULTS: Among 1227 BC patients, 129 (10.5%) had TNBC. TNBC patients had the worst OS (P: 0.0005) and DFS (P: 0.0016) among the subtypes. However, variations in race did not have any difference in OS or DFS among TNBC patients. Axillary lymph node involvement, invasive lobular histology, larger tumor size, and the presence of lymphovascular invasion (LVI) were factors associated with both poor DFS and OS among TNBC patients.
CONCLUSIONS: Racial variation did not have any impact on the prognosis of the TNBC.
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.