Performance of an offline systematic error correction strategy in pediatric patients receiving adjuvant conformal radiotherapy for Wilm's tumor.

BACKGROUND: Radiotherapy plays a key role as an adjuvant treatment in pediatric Wilm's tumor, improving both survival and quality of life. The success of radiotherapy depends on the precise delivery of radiation dose to the tumor while sparing radiosensitive structures in the vicinity of the tumor. Pediatric patients pose unique challenges in achieving accurate radiotherapy delivery due to their inability to understand instructions and the high radiosensitivity of their tissues. Thus, it is important to determine the optimum geometric verification strategy that will ensure accurate delivery of the prescribed target as specified in the patient's treatment plan. PURPOSE: To evaluate the performance of an offline geometric correction strategy in ensuring accuracy and reproducibility during radiotherapy delivery in Wilm's tumor patients. MATERIAL AND METHODS: The extended no-action level offline correction strategy was applied in the radiotherapy delivery of 45 Wilm's tumor patients. Gross errors from the first three fractions were used to calculate the mean errors which were then applied as offline correction factors. Mean errors among different groups were compared using a two-way analysis of variance (ANOVA) and Dunnett's pairwise comparisons. All statistical analyses and data visualization were performed using GraphPad Prism version 7 (Insight Partners, GraphPad Holdings, LLC). RESULTS: A total of 45 patients were included in the study. In all three orthogonal directions, the recorded gross errors were significantly lower after the application of the systematic error corrections. Random errors were significantly larger in the longitudinal direction compared to lateral (mean difference = 0.28, p = 0.036) and vertical directions (mean difference = 0.37 cm, p = 0.003). Patients' age was a significant predictor of random errors whereby the magnitude of random error decreased with increasing age. CONCLUSION: This study shows that the offline correction strategy used is effective in ensuring the accuracy of radiotherapy delivery in pediatric Wilm's tumor patients.

Views from Multidisciplinary Oncology Clinicians on Strengthening Cancer Care Delivery Systems in Tanzania.

BACKGROUND: In response to the increasing burden of cancer in Tanzania, the Ministry of Health, Community Development, Gender, Elderly and Children launched National Cancer Treatment Guidelines (TNCTG) in February 2020. The guidelines aimed to improve and standardize oncology care in the country. At Ocean Road Cancer Institute (ORCI), we developed a theory-informed implementation strategy to promote guideline-concordant care. As part of the situation analysis for implementation strategy development, we conducted focus group discussions to evaluate clinical systems and contextual factors that influence guideline-based practice prior to the launch of the TNCTG. MATERIALS AND METHODS: In June 2019, three focus group discussions were conducted with a total of 21 oncology clinicians at ORCI, stratified by profession. A discussion guide was used to stimulate dialogue about facilitators and barriers to delivery of guideline-concordant care. Discussions were audio recorded, transcribed, translated, and analyzed using thematic framework analysis. RESULTS: Participants identified factors both within the inner context of ORCI clinical systems and outside of ORCI. Themes within the clinical systems included capacity and infrastructure, information technology, communication, efficiency, and quality of services provided. Contextual factors external to ORCI included interinstitutional coordination, oncology capacity in peripheral hospitals, public awareness and beliefs, and financial barriers. Participants provided pragmatic suggestions for strengthening cancer care delivery in Tanzania. CONCLUSION: Our results highlight several barriers and facilitators within and outside of the clinical systems at ORCI that may affect uptake of the TNCTG. Our findings were used to inform a broader guideline implementation strategy, in an effort to improve uptake of the TNCTGs at ORCI. IMPLICATIONS FOR PRACTICE: This study provides an assessment of cancer care delivery systems in a low resource setting from the unique perspectives of local multidisciplinary oncology clinicians. Situational analysis of contextual factors that are likely to influence guideline implementation outcomes is the first step of developing an implementation strategy for cancer treatment guidelines. Many of the barriers identified in this study represent actionable targets that will inform the next phases of our implementation strategy for guideline-concordant cancer care in Tanzania and comparable settings.

Development of a theory-driven implementation strategy for cancer management guidelines in sub-Saharan Africa.

BACKGROUND: Despite recent international efforts to develop resource-stratified clinical practice guidelines for cancer, there has been little research to evaluate the best strategies for dissemination and implementation in low- and middle-income countries (LMICs). Guideline publication alone is insufficient. Extensive research has shown that structured, multifaceted implementation strategies that target barriers to guideline use are most likely to improve adherence; however, most of this research has been conducted in high-income countries. There is a pressing need to develop and evaluate guideline implementation strategies for cancer management in LMICs in order to address stark disparities in cancer outcomes. METHODS: In preparation for the launch of Tanzania's first National Cancer Treatment Guidelines, we developed a theory-driven implementation strategy for guideline-based practice at Ocean Road Cancer Institute (ORCI). Here, we use the Intervention Mapping framework to provide a detailed stepwise description of our process. First, we conducted a needs assessment to identify barriers and facilitators to guideline-based practice at ORCI. Second, we defined both proximal and performance objectives for our implementation strategy. Third, we used the Capability, Opportunity, Motivation and Behavior/Behavior Change Wheel (COM-B/BCW) framework to categorize the barriers and facilitators, choose behavior change techniques most likely to overcome targeted barriers and leverage facilitators, and select a feasible mode of delivery for each technique. Fourth, we organized these modes of delivery into a phased implementation strategy. Fifth, we operationalized each component of the strategy. Sixth, we identified the indicators of the process, outcome, and impact of our intervention and developed an evaluation plan to measure them using a mixed methods approach. DISCUSSION: We developed a robust, multifaceted guideline implementation strategy derived from a prominent behavior change theory for use in Tanzania. The barriers and strategies we generated are consistent with those well established in the literature, enhancing the validity and generalizability of our process and results. Through our rigorous evaluation plan and systematic account of modifications and adaptations, we will characterize the transferability of "proven" guideline implementation strategies to LMICs. We hope that by describing our process in detail, others may endeavor to replicate it, meeting a widespread need for dedicated efforts to implement cancer guidelines in LMICs.