Andrew Miller

PURPOSE: Oropharyngeal cancer is on the rise, despite declines in other head and neck cancers. The primary cause of this increase is human papillomavirus (HPV) infection, which accounts for over a quarter of new cancer patients in Tanzania. These cancers are largely preventable through HPV vaccination. HPV-associated oropharyngeal squamous cell carcinoma (OPSCC) is recognized as a distinct molecular and clinical entity, with unique demographics, staging, survival, and prognosis. International guidelines recommend that all staging, prognosis, and treatment decisions for OPSCC occur after determining the p16 expression, a surrogate immunohistochemical marker for HPV infection. However, current Tanzanian guidelines and clinical practice do not incorporate p16 immunohistochemistry (IHC) testing, despite the availability of qualified pathologists and laboratories. PATIENTS AND METHODS: This retrospective hospital-based cohort study was conducted at the Ocean Road Cancer Institute (ORCI) and Muhimbili National Hospital in Dar es Salaam, Tanzania. A total of 83 patients with OPSCC were included. We assessed the sociodemographic and clinicopathologic profiles and the impact of p16 expression on overall survival (OS) in patients with OPSCC treated at the ORCI. RESULTS: The prevalence of p16-positive OPSCC was found to be 43.4%. Patients with p16-positive tumors were younger and predominantly male and had a 3-year OS of 36% compared with 16.6% in those with p16-negative tumors. CONCLUSION: Our findings support the use of p16 IHC as a prognostic biomarker for OPSCC. In addition, the high prevalence of p16-positive OPSCC in our cohort suggests the broader implementation of gender-neutral HPV vaccination across Tanzania.

IntroductionFacilitators to implement shared cancer follow-up care into clinical practice include mechanisms to allow the oncologist to continue overseeing the care of their patient, two-way information sharing and clear follow-up protocols for general practitioners (GPs). This paper aimed to evaluate patients, GPs and radiation oncologists (ROs) acceptance of a shared care intervention. MethodsSemi-structured interviews were conducted pre- and post intervention with patients that were 3 years post radiotherapy treatment for breast, colorectal or prostate cancer, their RO, and their GP. Inductive and deductive thematical analysis was employed. ResultsThirty-two participants were interviewed (19 patients, 9 GPs, and 4 ROs). Pre intervention, there was support for GPs to play a greater role in cancer follow-up care, however, patients were concerned about the GPs cancer-specific skills. Patients, GPs and ROs were concerned about increasing the GPs workload. Post intervention, participants were satisfied that the GPs had specific skills and that the impact on GP workload was comparable to writing a referral. However, GPs expressed concern about remuneration. GPs and ROs felt the model provided patient choice and were suitable for low-risk, stable patients around 2-3 years post treatment. Patients emphasised that they trusted their RO to advise them on the most appropriate follow-up model suited to their individual situation. The overall acceptance of shared care depended on successful health technology to connect the GP and RO. There were no differences in patient acceptance between rural, regional, and cancer types. ROs presented differences in acceptance for the different cancer types, with breast cancer strongly supported. ConclusionPatients, GPs and ROs felt this shared cancer follow-up model of care was acceptable, but only if the RO remained directly involved and the health technology worked. There is a need to review funding and advocate for health technology advances to support integration. Patient or Public ContributionPatients treated with curative radiotherapy for breast, colorectal and prostate cancer, their RO and their GPs were actively involved in this study by giving their consent to be interviewed.

Introduction COVID-19 required health services to be innovative and quickly adapt their health service delivery, including adopting health technology in cancer clinical practice. COVID-19 restrictions forced us to introduce follow-up consultations for many patients via telehealth. At the same time, we adapted an existing Patient Reported Outcome messaging service that linked to the patient’s medical record to allow patients to self-report their health and disease status before their telehealth follow-up consultation. This study aimed to evaluate the feasibility of self-reporting for cancer follow-up care, and determine the patient-clinician level of agreement. Methods Cross-sectional clinical practice study. Patients on radiation oncology follow-up care were sent a text message with a weblink to a survey to self-report their health before their radiation oncologist appointment. Radiation oncologists completed the same set of questions during or within a day of the telehealth follow-up consultation. Descriptive statistics were analysed to evaluate the uptake of self-reporting. Percent agreement and Cohen’s Kappa were used to determine patient-clinician agreement. Results A moderate response rate of 62% was achieved from the 145 patients. There was no difference in the age of patients that were able to complete the assessment. Percent agreement between the patient-reported and the clinician-reported for weight change, appetite, physical performance, side effects was acceptable (>75%). However, percent agreement was moderate for pain and sleep. For most items, Cohen’s Kappa indicated moderate agreement, with pain, side effects, and recurrence being fair. Patients were more likely to report themselves worse than the clinician for all items, except for side effects. Conclusion Patient self-reported health can provide useful information for clinicians to remotely follow-up their patients. This holds promise for future models of follow-up care, particularly for rural and remote patients, and during pandemics and other disasters where clinic attendance is not possible.

Objective: To evaluate treatment outcomes in patients from a low-middle income country (LMIC) with esophageal carcinoma who underwent esophagectomy after neoadjuvant chemoradiation (NACRT/S). Methods: Between 2010 and 2020, 254 patients (median follow-up: 53 months) met our inclusion criteria. Out-of-field nodal regions were determined by reviewing individual radiotherapy plans. Cox regression modelling was performed to analyze overall survival (OS) and recurrence-free survival (RFS), while pathological complete response (pCR) prediction utilized Poisson regression. Results: The median OS was 71.4 months (interquartile range: 19.6–∞), RFS did not reach the median and pCR rate was 46%. On multivariable Cox regression, BMI [0.93 (0.89–0.98); 0.94 (0.89–0.99)] and absence of out-of-field node with extranodal extension (ENE)[0.22 (0.09–0.53); 0.30 (0.12–0.75)] influenced OS and RFS, respectively. Age [1.03 (1.01–1.06)], nodal stage [cN2-3 vs cN0: 2.67 (1.08–6.57)] and adventitial involvement [2.54 (1.36–4.72)] also influenced OS, while involved margins [3.12 (1.24–7.81)] influenced RFS. On multivariable Poisson regression, non-CROSS-chemotherapy regimens [0.65 (0.44–0.95)] and residual primary disease on pre-surgical imaging [0.73 (0.57–0.93)] were significantly associated with pCR. The most frequently involved in-field and out-of-field nodal regions were the periesophageal and perigastric (greater and lesser curvature) regions, respectively. Conclusion: NACRT/S is feasible and effective in patients from LMIC. Out-of-field ENE merits further investigation as a prognostic factor since it significantly influenced both OS and RFS. Advances in knowledge: The results of clinical trials are replicable in LMICs. Out-of-field ENE is an independent prognostic factor for OS and RFS.

(1) Background: Patients treated with radiotherapy require follow-up care to detect and treat acute and late side effects, and to monitor for recurrence. The increasing demand for follow-up care poses a challenge for specialists and general practitioners. There is a perception that general practitioners do not have the specialised knowledge of treatment side effects and how to manage these. Knowing the concordance between general practitioner and oncologist clinical assessments can improve confidence in healthcare professionals. This study aimed to measure the level of agreement between general practitioners and radiation oncologists using a standardised clinical assessment; (2) Methods: a cross-sectional clinical practice study; sample aim of 20 breast, prostate or colorectal patients, three years post-radiotherapy treatment; their general practitioner and radiation oncologist; (3) Results: There was acceptable percent agreement (>75%) and a moderate to almost perfect agreement (Fleiss kappa) for all variables between the 15 general practitioner-radiation oncologist dyads; (4) Conclusions: The general practitioner and radiation oncologist concordance of a clinical follow-up assessment for radiation oncology patients is an important finding. These results can reassure both general practitioners and oncologists that general practitioners can provide cancer follow-up care. However, further studies are warranted to confirm the findings and improve reassurance for health professionals.

Summary: Introduction: There is significant potential to analyse and model routinely collected data for radiotherapy patients to provide evidence to support clinical decisions, particularly where clinical trials evidence is limited or non‐existent. However, in practice there are administrative, ethical, technical, logistical and legislative barriers to having coordinated data analysis platforms across radiation oncology centres.Methods: A distributed learning network of computer systems is presented, with software tools to extract and report on oncology data and to enable statistical model development. A distributed or federated learning approach keeps data in the local centre, but models are developed from the entire cohort.Results: The feasibility of this approach is demonstrated across six Australian oncology centres, using routinely collected lung cancer data from oncology information systems. The infrastructure was used to validate and develop machine learning for model‐based clinical decision support and for one centre to assess patient eligibility criteria for two major lung cancer radiotherapy clinical trials (RTOG‐9410, RTOG‐0617). External validation of a 2‐year overall survival model for non–small cell lung cancer (NSCLC) gave an AUC of 0.65 and C‐index of 0.62 across the network. For one centre, 65% of Stage III NSCLC patients did not meet eligibility criteria for either of the two practice‐changing clinical trials, and these patients had poorer survival than eligible patients (10.6 m vs. 15.8 m, P = 0.024).Conclusion: Population‐based studies on routine data are possible using a distributed learning approach. This has the potential for decision support models for patients for whom supporting clinical trial evidence is not applicable.

Background: The rising incidence of cancer and increasing numbers of cancer survivors have resulted in the need to find alternative models of care for cancer follow-up care. The acceptability for follow-up care in general practice is growing, and acceptance increases with shared-care models where oncologists continue to oversee the care. However, a major barrier to this model is the effective exchange of information in real time between oncologists and general practitioners. Improved communication technology plays an important role in the acceptability and feasibility of shared cancer follow-up care. Objective: The aim of this study is to evaluate the feasibility and acceptability of a shared cancer follow-up model of care between patients, general practitioners and radiation oncologists. Methods: This is a mixed methods, multisite implementation study exploring shared follow-up care for breast, colorectal, and prostate cancer patients treated with curative radiotherapy in New South Wales, Australia. This study uses web-based technology to support general practitioners in performing some aspects of routine radiotherapy follow-up care, while being overseen by a radiation oncologist in real time. The study has two phases: Phase 1 is designed to establish the level of agreement between general practitioners and radiation oncologists and Phase 2 is designed to implement shared follow-up care into practice and to evaluate this implementation. Results: Recruitment of radiation oncologists, patients, and general practitioners commenced in December 2020 and will continue until February 2021. Data collection will occur during 2021, and data will be ready for analysis by the end of 2021. Conclusions: Few studies have investigated the role of health technologies in supporting communication deficiencies for shared cancer follow-up care. The implementation and evaluation of models of care need to be conducted using a person-centered approach that is responsive to patients’ preferences and needs. Should the findings of the study be acceptable and feasible to radiation oncologists, general practitioners, and patients, it can be quickly implemented and expanded to other tumor groups or to medical oncology and hematology. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12620001083987; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380057 International Registered Report Identifier (IRRID): PRR1-10.2196/21752

Objective: This study compares planning techniques stratified by consensus delineation guidelines in patients undergoing whole-breast radiotherapy based on an objective plan quality assessment scale. Methods: 10 patients with left-sided breast cancer were randomly selected, and target delineation for intact breast was performed using Tangent (RTOG 0413), ESTRO, and RTOG guidelines. Consensus Plan Quality Metric (PQM) scoring was defined and communicated to the physicist before commencing treatment planning. Field-in-field IMRT (FiF), inverse IMRT (IMRT) and volumetric modulated arc therapy (VMAT) plans were created for each delineation. Statistical analyses utilised a two-way repeated measures analysis of variance, after applying a Bonferroni correction. Results: Total PQM score of plans for Tangent and ESTRO were comparable for FiF and IMRT techniques (FiF vs IMRT for Tangent, p = 0.637; FiF vs IMRT for ESTRO, p = 0.304), and were also significantly higher compared to VMAT. Total PQM score of plans for RTOG revealed that IMRT planning achieved a significantly higher score compared to both FiF and VMAT (IMRT vs FiF, p < 0.001; IMRT vs VMAT, p < 0.001). Conclusions: Total PQM scores were equivalent for FiF and IMRT for both Tangent and ESTRO delineations, whereas IMRT was best suited for RTOG delineation. Advances in knowledge: FiF and IMRT planning techniques are best suited for ESTRO or Tangent delineations. IMRT also yields better results with RTOG delineation.