Lung cancer (internet-based) Delphi (LUCiD): A modified eDelphi consensus process to establish Australasian clinical quality indicators for thoracic cancer.

BACKGROUND AND OBJECTIVE: Approximately 16,000 new cases of lung cancer are diagnosed each year in Australia and Aotearoa New Zealand, and it is the leading cause of cancer death in the region. Unwarranted variation in lung cancer care and outcomes has been described for many years, although clinical quality indicators to facilitate benchmarking across Australasia have not been established. The purpose of this study was to establish clinical quality indicators applicable to lung and other thoracic cancers across Australia and Aotearoa New Zealand. METHODS: Following a literature review, a modified three round eDelphi consensus process was completed between October 2022 and June 2023. Participants included clinicians from all relevant disciplines, patient advocates, researchers and other stakeholders, with representatives from all Australian states and territories and Aotearoa New Zealand. Consensus was set at a threshold of 70%, with the first two rounds conducted as online surveys, and the final round held as a hybrid in person and virtual consensus meeting. RESULTS: The literature review identified 422 international thoracic oncology indicators, and a total of 71 indicators were evaluated over the course of the Delphi consensus. Ultimately, 27 clinical quality indicators reached consensus, covering the continuum of thoracic oncologic care from diagnosis to first line treatment. Indicators benchmarking supportive care were poorly represented. Attendant numeric quality standards were developed to facilitate benchmarking. CONCLUSION: Twenty-seven clinical quality indicators relevant to thoracic oncology care in Australasia were developed. Real world implementation will now be explored utilizing a prospective dataset collected across Australia.

Infrastructure platform for privacy-preserving distributed machine learning development of computer-assisted theragnostics in cancer.

INTRODUCTION: Emerging evidence suggests that data-driven support tools have found their way into clinical decision-making in a number of areas, including cancer care. Improving them and widening their scope of availability in various differing clinical scenarios, including for prognostic models derived from retrospective data, requires co-ordinated data sharing between clinical centres, secondary analyses of large multi-institutional clinical trial data, or distributed (federated) learning infrastructures. A systematic approach to utilizing routinely collected data across cancer care clinics remains a significant challenge due to privacy, administrative and political barriers. METHODS: An information technology infrastructure and web service software was developed and implemented which uses machine learning to construct clinical decision support systems in a privacy-preserving manner across datasets geographically distributed in different hospitals. The infrastructure was deployed in a network of Australian hospitals. A harmonized, international ontology-linked, set of lung cancer databases were built with the routine clinical and imaging data at each centre. The infrastructure was demonstrated with the development of logistic regression models to predict major cardiovascular events following radiation therapy. RESULTS: The infrastructure implemented forms the basis of the Australian computer-assisted theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning. Four radiation oncology departments (across seven hospitals) in New South Wales (NSW) participated in this demonstration study. Infrastructure was deployed at each centre and used to develop a model predicting for cardiovascular admission within a year of receiving curative radiotherapy for non-small cell lung cancer. A total of 10,417 lung cancer patients were identified with 802 being eligible for the model. Twenty features were chosen for analysis from the clinical record and linked registries. After selection, 8 features were included and a logistic regression model achieved an area under the receiver operating characteristic (AUROC) curve of 0.70 and C-index of 0.65 on out-of-sample data. CONCLUSION: The infrastructure developed was demonstrated to be usable in practice between clinical centres to harmonize routinely collected oncology data and develop models with federated learning. It provides a promising approach to enable further research studies in radiation oncology using real world clinical data.

Translation of oncology multidisciplinary team meeting (MDM) recommendations into clinical practice.

BACKGROUND: Multidisciplinary team meeting (MDM) processes differ according to clinical setting and tumour site. This can impact on decision making. This study aimed to evaluate the translation of MDM recommendations into clinical practice across solid tumour MDMs at an academic centre. METHODS: A retrospective audit of oncology records was performed for nine oncology MDMs held at Liverpool Hospital, NSW, Australia from 1/2/17-31/7/17. Information was collected on patient factors (age, gender, country of birth, language, postcode, performance status, comorbidities), tumour factors (diagnosis, stage) and MDM factors (number of MDMs, MDM recommendation). Management was audited up to a year post MDM to record management and identify reasons if discordant with MDM recommendations. Univariate and multivariable regression analyses were performed to assess for factors associated with concordant management. RESULTS: Eight hundred thirty-five patients were discussed, median age was 65 years and 51.4% were males. 70.8% of patients were presented at first diagnosis, 77% discussed once and treatment recommended in 73.2%. Of 771 patients assessable for concordance, management was fully concordant in 79.4%, partially concordant in 12.8% and discordant in 7.8%. Concordance varied from 84.5% for lung MDM to 97.6% for breast MDMs. On multivariable analysis, breast and upper GI MDMs and discussion at multiple MDMs were significantly associated with concordant management. The most common reason for discordant management was patient/guardian decision (28.3%). CONCLUSION: There was variability in translation of MDM recommendations into clinical practice by tumour site. Routine measurement of implementation of MDM recommendations should be considered as a quality indicator of MDM practice.

Radiotherapy treatment for lung cancer: Current status and future directions.

Radiotherapy is an important modality used for the treatment of lung cancer. Seventy-seven percent of all patients with lung cancer have an evidence-based indication for radiotherapy, although it is often underutilized. Radiotherapy can be used as curative or palliative treatment across all stages of disease. Technological advances have allowed better radiotherapy targeting of tumours and reduced incidental irradiation of surrounding normal tissues. This has expanded the indications for radiotherapy in lung cancer and improved outcomes both in terms of increasing survival and reducing toxicity. This review examines the current role of radiotherapy in lung cancer, discusses the evidence behind this and identifies future directions in the radiotherapy treatment of lung cancer.

Stereotactic ablative radiotherapy versus standard radiotherapy in stage 1 non-small-cell lung cancer (TROG 09.02 CHISEL): a phase 3, open-label, randomised controlled trial.

BACKGROUND: Stereotactic ablative body radiotherapy (SABR) is widely used to treat inoperable stage 1 non-small-cell lung cancer (NSCLC), despite the absence of prospective evidence that this type of treatment improves local control or prolongs overall survival compared with standard radiotherapy. We aimed to compare the two treatment techniques. METHODS: We did this multicentre, phase 3, randomised, controlled trial in 11 hospitals in Australia and three hospitals in New Zealand. Patients were eligible if they were aged 18 years or older, had biopsy-confirmed stage 1 (T1-T2aN0M0) NSCLC diagnosed on the basis of 18F-fluorodeoxyglucose PET, and were medically inoperable or had refused surgery. Patients had to have an Eastern Cooperative Oncology Group performance status of 0 or 1, and the tumour had to be peripherally located. Patients were randomly assigned after stratification for T stage and operability in a 2:1 ratio to SABR (54 Gy in three 18 Gy fractions, or 48 Gy in four 12 Gy fractions if the tumour was <2 cm from the chest wall) or standard radiotherapy (66 Gy in 33 daily 2 Gy fractions or 50 Gy in 20 daily 2·5 Gy fractions, depending on institutional preference) using minimisation, so no sequence was pre-generated. Clinicians, patients, and data managers had no previous knowledge of the treatment group to which patients would be assigned; however, the treatment assignment was subsequently open label (because of the nature of the interventions). The primary endpoint was time to local treatment failure (assessed according to Response Evaluation Criteria in Solid Tumors version 1.0), with the hypothesis that SABR would result in superior local control compared with standard radiotherapy. All efficacy analyses were based on the intention-to-treat analysis. Safety analyses were done on a per-protocol basis, according to treatment that the patients actually received. The trial is registered with ClinicalTrials.gov (NCT01014130) and the Australia and New Zealand Clinical Trials Registry (ACTRN12610000479000). The trial is closed to new participants. FINDINGS: Between Dec 31, 2009, and June 22, 2015, 101 eligible patients were enrolled and randomly assigned to receive SABR (n=66) or standard radiotherapy (n=35). Five (7·6%) patients in the SABR group and two (6·5%) in the standard radiotherapy group did not receive treatment, and a further four in each group withdrew before study end. As of data cutoff (July 31, 2017), median follow-up for local treatment failure was 2·1 years (IQR 1·2-3·6) for patients randomly assigned to standard radiotherapy and 2·6 years (IQR 1·6-3·6) for patients assigned to SABR. 20 (20%) of 101 patients had progressed locally: nine (14%) of 66 patients in the SABR group and 11 (31%) of 35 patients in the standard radiotherapy group, and freedom from local treatment failure was improved in the SABR group compared with the standard radiotherapy group (hazard ratio 0·32, 95% CI 0·13-0·77, p=0·0077). Median time to local treatment failure was not reached in either group. In patients treated with SABR, there was one grade 4 adverse event (dyspnoea) and seven grade 3 adverse events (two cough, one hypoxia, one lung infection, one weight loss, one dyspnoea, and one fatigue) related to treatment compared with two grade 3 events (chest pain) in the standard treatment group. INTERPRETATION: In patients with inoperable peripherally located stage 1 NSCLC, compared with standard radiotherapy, SABR resulted in superior local control of the primary disease without an increase in major toxicity. The findings of this trial suggest that SABR should be the treatment of choice for this patient group. FUNDING: The Radiation and Optometry Section of the Australian Government Department of Health with the assistance of Cancer Australia, and the Cancer Society of New Zealand and the Cancer Research Trust New Zealand (formerly Genesis Oncology Trust).

Palliative care and psychosocial care in metastatic non-small cell lung cancer: factors affecting utilisation of services and impact on patient survival.

BACKGROUND: Palliative care (PC) and psychosocial care (PSC) are essential services, which can positively impact on quality of life in patients with metastatic lung cancer, when advanced disease and poor prognosis preclude the use of curative therapies. The aims of this study were to describe patterns of PC and PSC and identify factors associated with service utilisation and overall patient survival. METHOD: A retrospective Australian cohort of South Western Sydney residents with newly diagnosed stage IV non-small cell lung cancer (NSCLC) in 2006-2012 was identified from the Local Health District Clinical Cancer Registry. Supplemental information was sourced from the area PC database and hospital medical records. Cox regression models with robust variance identified factors associated with PC and PSC and examined patient survival. RESULTS: A total of 923 patients were identified. Eighty-three per cent of patients were seen by PC, with 67% seen within 8 weeks of diagnosis. PSC utilisation was 82%. Radiotherapy treatment and residential area were associated with both PC and PSC. Increasing age was associated with early PC referral. Median overall survival was 4 months. PC was associated with patient survival; however, the effect varied over time. CONCLUSION: The rate of PC and PSC in our metastatic NSCLC population was high when compared with published data. Despite this, there were gaps in PC and PSC provision in this population, notably with patients not receiving active treatment, and those receiving systemic therapy utilising these services less frequently. PSC and PC contact were not convincingly associated with improved patient survival.

A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy.

BACKGROUND: Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate the performance of a previously published model for early death in our cohorts. Second, to develop a prognostic model for early death prediction following radiotherapy. MATERIAL AND METHODS: Patients with NSCLC treated with chemoradiotherapy or radiotherapy alone were included in this study. Four different cohorts from different countries were available for this work (N = 1540). The previous model used age, gender, performance status, tumor stage, income deprivation, no previous treatment given (yes/no) and body mass index to make predictions. A random forest model was developed by learning on the Maastro cohort (N = 698). The new model used performance status, age, gender, T and N stage, total tumor volume (cc), total tumor dose (Gy) and chemotherapy timing (none, sequential, concurrent) to make predictions. Death within 4 months of receiving the first radiotherapy fraction was used as the outcome. RESULTS: Early death rates ranged from 6 to 11% within the four cohorts. The previous model performed with AUC values ranging from 0.54 to 0.64 on the validation cohorts. Our newly developed model had improved AUC values ranging from 0.62 to 0.71 on the validation cohorts. CONCLUSIONS: Using advanced machine learning methods and informative variables, prognostic models for early mortality can be developed. Development of accurate prognostic tools for early mortality is important to inform patients about treatment options and optimize care.

A narrative synthesis of the quality of cancer care and development of an integrated conceptual framework.

The general paradigms that exist to guide measures in quality of care do not sufficiently deal with the changing needs of cancer management. The aim of this study was to review the literature regarding the quality of cancer care and develop a conceptual framework relevant to current practice. A textual narrative review of the literature was conducted by searching electronic databases from the last 10 years. Articles were then screened and included if they were both relevant to the management of cancer and standards in quality of care. Thematic analysis of the included articles was performed. Eighty-three articles were included and 12 domains identified and integrated with current models to develop a conceptual framework. These included: healthcare delivery system; timeliness; access; appropriateness of care; multidisciplinary and coordinated care; patient experience; technical aspects; safety; patient-centred outcomes; disease-specific outcomes; innovation and improvement and value. We propose a conceptual framework for the quality of cancer care based on relevant and current oncology practice. This presents a more practical and comprehensive approach than general models, and can be used by healthcare providers, managers and policy makers to guide and identify the need for metrics for quality improvements.

A randomised phase II trial of Stereotactic Ablative Fractionated radiotherapy versus Radiosurgery for Oligometastatic Neoplasia to the lung (TROG 13.01 SAFRON II).

BACKGROUND: Stereotactic ablative body radiotherapy (SABR) is emerging as a non-invasive method for precision irradiation of lung tumours. However, the ideal dose/fractionation schedule is not yet known. The primary purpose of this study is to assess safety and efficacy profile of single and multi-fraction SABR in the context of pulmonary oligometastases. METHODS/DESIGN: The TROG 13.01/ALTG 13.001 clinical trial is a multicentre unblinded randomised phase II study. Eligible patients have up to three metastases to the lung from any non-haematological malignancy, each < 5 cm in size, non-central targets, and have all primary and extrathoracic disease controlled with local therapies. Patients are randomised 1:1 to a single fraction of 28Gy versus 48Gy in four fractions of SABR. The primary objective is to assess the safety of each treatment arm, with secondary objectives including assessment of quality of life, local efficacy, resource use and costs, overall and disease free survival and time to distant failure. Outcomes will be stratified by number of metastases and origin of the primary disease (colorectal versus non-colorectal primary). Planned substudies include an assessment of the impact of online e-Learning platforms for lung SABR and assessment of the effect of SABR fractionation on the immune responses. A total of 84 patients are required to complete the study. DISCUSSION: Fractionation schedules have not yet been investigated in a randomised fashion in the setting of oligometastatic disease. Assuming the likelihood of similar clinical efficacy in both arms, the present study design allows for exploration of the hypothesis that cost implications of managing potentially increased toxicities from single fraction SABR will be outweighed by costs associated with delivering multiple-fraction SABR. TRIALS REGISTRATION: ACTRN12613001157763 , registered 17th October 2013.

Psychological distress and quality of life in lung cancer: the role of health-related stigma, illness appraisals and social constraints.

OBJECTIVE: Health-related stigma is associated with negative psychological and quality of life outcomes in lung cancer patients. This study describes the impact of stigma on lung cancer patients' psychological distress and quality of life and explores the role of social constraints and illness appraisal as mediators of effect. METHODS: A self-administered cross-sectional survey examined psychological distress and quality of life in 151 people (59% response rate) diagnosed with lung cancer from Queensland and New South Wales. Health-related stigma, social constraints and illness appraisals were assessed as predictors of adjustment outcomes. RESULTS: Forty-nine percent of patients reported elevated anxiety; 41% were depressed; and 51% had high global distress. Health-related stigma was significantly related to global psychological distress and quality of life with greater stigma and shame related to poorer outcomes. These effects were mediated by illness appraisals and social constraints. CONCLUSIONS: Health-related stigma appears to contribute to poorer adjustment by constraining interpersonal discussions about cancer and heightening feelings of threat. There is a need for the development and evaluation of interventions to ameliorate the negative effects of health-related stigma among lung cancer patients.

Faster and lower dose imaging: evaluating adaptive, constant gantry velocity and angular separation in fast low-dose 4D cone beam CT imaging.

BACKGROUND: The adoption of four-dimensional cone beam computed tomography (4DCBCT) for image-guided lung cancer radiotherapy is increasing, especially for hypofractionated treatments. However, the drawbacks of 4DCBCT include long scan times (∼240 s), inconsistent image quality, higher imaging dose than necessary, and streaking artifacts. With the emergence of linear accelerators that can acquire 4DCBCT scans in a short period of time (9.2 s) there is a need to examine the impact that these very fast gantry rotations have on 4DCBCT image quality. PURPOSE: This study investigates the impact of gantry velocity and angular separation between x-ray projections on image quality and its implication for fast low-dose 4DCBCT with emerging systems, such as the Varian Halcyon that provide fast gantry rotation and imaging. Large and uneven angular separation between x-ray projections is known to reduce 4DCBCT image quality through increased streaking artifacts. However, it is not known when angular separation starts degrading image quality. The study assesses the impact of constant and adaptive gantry velocity and determines the level when angular gaps impair image quality using state-of-the-art reconstruction methods. METHODS: This study considers fast low-dose 4DCBCT acquisitions (60-80 s, 200-projection scans). To assess the impact of adaptive gantry rotations, the angular position of x-ray projections from adaptive 4DCBCT acquisitions from a 30-patient clinical trial were analyzed (referred to as patient angular gaps). To assess the impact of angular gaps, variable and static angular gaps (20°, 30°, 40°) were introduced into evenly separated 200 projections (ideal angular separation). To simulate fast gantry rotations, which are on emerging linacs, constant gantry velocity acquisitions (9.2 s, 60 s, 120 s, 240 s) were simulated by sampling x-ray projections at constant intervals using the patient breathing traces from the ADAPT clinical trial (ACTRN12618001440213). The 4D Extended Cardiac-Torso (XCAT) digital phantom was used to simulate projections to remove patient-specific image quality variables. Image reconstruction was performed using Feldkamp-Davis-Kress (FDK), McKinnon-Bates (MKB), and Motion-Compensated-MKB (MCMKB) algorithms. Image quality was assessed using Structural Similarity-Index-Measure (SSIM), Contrast-to-Noise-Ratio (CNR), Signal-to-Noise-Ratio (SNR), Tissue-Interface-Width-Diaphragm (TIW-D), and Tissue-Interface-Width-Tumor (TIW-T). RESULTS: Patient angular gaps and variable angular gap reconstructions produced similar results to ideal angular separation reconstructions, while static angular gap reconstructions produced lower image quality metrics. For MCMKB-reconstructions, average patient angular gaps produced SSIM-0.98, CNR-13.6, SNR-34.8, TIW-D-1.5 mm, and TIW-T-2.0 mm, static angular gap 40° produced SSIM-0.92, CNR-6.8, SNR-6.7, TIW-D-5.7 mm, and TIW-T-5.9 mm and ideal produced SSIM-1.00, CNR-13.6, SNR-34.8, TIW-D-1.5 mm, and TIW-T-2.0 mm. All constant gantry velocity reconstructions produced lower image quality metrics than ideal angular separation reconstructions regardless of the acquisition time. Motion compensated reconstruction (MCMKB) produced the highest contrast images with low streaking artifacts. CONCLUSION: Very fast 4DCBCT scans can be acquired provided that the entire scan range is adaptively sampled, and motion-compensated reconstruction is performed. Importantly, the angular separation between x-ray projections within each individual respiratory bin had minimal effect on the image quality of fast low-dose 4DCBCT imaging. The results will assist the development of future 4DCBCT acquisition protocols that can now be achieved in very short time frames with emerging linear accelerators.

Radiotherapy protocol compliance in routine clinical practice for patients with stages I-III non-small-cell lung cancer.

INTRODUCTION: Despite the availability of radiotherapy treatment protocols for lung cancer, considerable treatment variation occurs in clinical practice. This study assessed compliance with a radiotherapy protocol for the treatment of patients with stages I-III non-small-cell lung cancer (NSCLC) in routine clinical practice and to identify factors that were associated with compliance. METHODS: The Cancer Institute New South Wales eviQ treatment protocol for external beam radiotherapy of stages I-III NSCLC was taken as the reference to measure compliance. All inoperable patients with stages I-III NSCLC and documented ECOG performance status treated with radiotherapy between 2007 and 2019 at two radiotherapy facilities were available for analysis. Protocol compliance rates were calculated. Univariate and multivariate logistic regression models with 23 input factors were used to determine factors significantly associated with compliance. Survival analysis was conducted for both compliant and non-compliant treatments. RESULTS: Overall, 656 patients met the inclusion criteria. Protocol compliance was 16%. Alternative dose/fractionation was responsible for 49% of non-compliant treatments with 30% receiving an alternative curative fractionation. Five of 23 factors (age at the start of radiotherapy, stage group, ECOG performance status, tumour location and alcoholism history) showed significant associations with protocol compliance on multivariate analysis. There was no significant difference in median survival between patients receiving protocol compliant treatment (15.1 months) and non-compliant treatment (15.6 months). CONCLUSION: Adherence to the eviQ curative radiotherapy protocol for stages I-III NSCLC was low. Alternative dose/fractionation schemes were the main reason for non-compliance. Protocol compliance was not associated with outcome.

Measurement that matters: A systematic review and modified Delphi of multidisciplinary colorectal cancer quality indicators.

AIM: To develop a priority set of quality indicators (QIs) for use by colorectal cancer (CRC) multidisciplinary teams (MDTs). METHODS: The review search strategy was executed in four databases from 2009-August 2019. Two reviewers screened abstracts/manuscripts. Candidate QIs and characteristics were extracted using a tailored abstraction tool and assessed for scientific soundness. To prioritize candidate indicators, a modified Delphi consensus process was conducted. Consensus was sought over two rounds; (1) multidisciplinary expert workshops to identify relevance to Australian CRC MDTs, and (2) an online survey to prioritize QIs by clinical importance. RESULTS: A total of 93 unique QIs were extracted from 118 studies and categorized into domains of care within the CRC patient pathway. Approximately half the QIs involved more than one discipline (52.7%). One-third of QIs related to surgery of primary CRC (31.2%). QIs on supportive care (6%) and neoadjuvant therapy (6%) were limited. In the Delphi Round 1, workshop participants (n = 12) assessed 93 QIs and produced consensus on retaining 49 QIs including six new QIs. In Round 2, survey participants (n = 44) rated QIs and prioritized a final 26 QIs across all domains of care and disciplines with a concordance level > 80%. Participants represented all MDT disciplines, predominantly surgical (32%), radiation (23%) and medical (20%) oncology, and nursing (18%), across six Australian states, with an even spread of experience level. CONCLUSION: This study identified a large number of existing CRC QIs and prioritized the most clinically relevant QIs for use by Australian MDTs to measure and monitor their performance.

The histopathological spectrum and molecular changes associated with KRAS G12C mutation in non-small cell lung carcinoma.

KRAS G12C is the most common KRAS mutation in non-small cell lung carcinoma (NSCLC), for which targeted therapy has recently been developed. From the 732 cases of NSCLC that underwent next-generation sequencing at the Department of Anatomical Pathology, Liverpool Hospital, between July 2021 and May 2023, we retrieved 83 (11%) consecutive cases of KRAS G12C mutated NSCLC, and analysed their clinical, pathological, and molecular features. Of the 83 cases of KRAS G12C mutated NSCLC, there were 46 (55%) men and 37 (45%) women, with mean age of 72 years. Of the 49 cases with known clinical information, 94% were current or ex-smokers, and 49% were stage IV at diagnosis with median survival of 12 months. Sixty-three percent were histology cases and the remainder were cytology cases. Eighty-two percent were non-mucinous adenocarcinomas, with conventional histology including lepidic, acinar, solid, single cells and micropapillary patterns, and 62% were poorly differentiated. There were five (6%) cases of mucinous adenocarcinoma, one case of pleomorphic carcinoma and one case of high-grade fetal adenocarcinoma. TTF1 was positive in the majority (89%) of cases. Nineteen (23%) cases had TP53 co-mutation, and these cases had trends towards higher PD-L1 expression, poor differentiation, and presentation as stage IV disease, but the differences were not statistically significant. KRAS G12C mutated NSCLCs almost exclusively occurred in smokers and were mostly non-mucinous adenocarcinomas with conventional histological patterns which ranged from well to poorly differentiated. Around a quarter had TP53 co-mutation, the histological impacts and immune profile of which need to be assessed in a larger study.

Uncertainty estimation using a 3D probabilistic U-Net for segmentation with small radiotherapy clinical trial datasets.

BACKGROUND AND OBJECTIVES: Bio-medical image segmentation models typically attempt to predict one segmentation that resembles a ground-truth structure as closely as possible. However, as medical images are not perfect representations of anatomy, obtaining this ground truth is not possible. A surrogate commonly used is to have multiple expert observers define the same structure for a dataset. When multiple observers define the same structure on the same image there can be significant differences depending on the structure, image quality/modality and the region being defined. It is often desirable to estimate this type of aleatoric uncertainty in a segmentation model to help understand the region in which the true structure is likely to be positioned. Furthermore, obtaining these datasets is resource intensive so training such models using limited data may be required. With a small dataset size, differing patient anatomy is likely not well represented causing epistemic uncertainty which should also be estimated so it can be determined for which cases the model is effective or not. METHODS: We use a 3D probabilistic U-Net to train a model from which several segmentations can be sampled to estimate the range of uncertainty seen between multiple observers. To ensure that regions where observers disagree most are emphasised in model training, we expand the Generalised Evidence Lower Bound (ELBO) with a Constrained Optimisation (GECO) loss function with an additional contour loss term to give attention to this region. Ensemble and Monte-Carlo dropout (MCDO) uncertainty quantification methods are used during inference to estimate model confidence on an unseen case. We apply our methodology to two radiotherapy clinical trial datasets, a gastric cancer trial (TOPGEAR, TROG 08.08) and a post-prostatectomy prostate cancer trial (RAVES, TROG 08.03). Each dataset contains only 10 cases each for model development to segment the clinical target volume (CTV) which was defined by multiple observers on each case. An additional 50 cases are available as a hold-out dataset for each trial which had only one observer define the CTV structure on each case. Up to 50 samples were generated using the probabilistic model for each case in the hold-out dataset. To assess performance, each manually defined structure was matched to the closest matching sampled segmentation based on commonly used metrics. RESULTS: The TOPGEAR CTV model achieved a Dice Similarity Coefficient (DSC) and Surface DSC (sDSC) of 0.7 and 0.43 respectively with the RAVES model achieving 0.75 and 0.71 respectively. Segmentation quality across cases in the hold-out datasets was variable however both the ensemble and MCDO uncertainty estimation approaches were able to accurately estimate model confidence with a p-value < 0.001 for both TOPGEAR and RAVES when comparing the DSC using the Pearson correlation coefficient. CONCLUSIONS: We demonstrated that training auto-segmentation models which can estimate aleatoric and epistemic uncertainty using limited datasets is possible. Having the model estimate prediction confidence is important to understand for which unseen cases a model is likely to be useful.

Outcome prediction models incorporating clinical variables for Head and Neck Squamous cell Carcinoma: A systematic review of methodological conduct and risk of bias.

Multiple outcome prediction models have been developed for Head and Neck Squamous Cell Carcinoma (HNSCC). This systematic review aimed to identify HNSCC outcome prediction model studies, assess their methodological quality and identify those with potential utility for clinical practice. Inclusion criteria were mucosal HNSCC prognostic prediction model studies (development or validation) incorporating clinically available variables accessible at time of treatment decision making and predicting tumour-related outcomes. Eligible publications were identified from PubMed and Embase. Methodological quality and risk of bias were assessed using the checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies (CHARMS) and prediction model risk of bias assessment tool (PROBAST). Eligible publications were categorised by study type for reporting. 64 eligible publications were identified; 55 reported model development, 37 external validations, with 28 reporting both. CHARMS checklist items relating to participants, predictors, outcomes, handling of missing data, and some model development and evaluation procedures were generally well-reported. Less well-reported were measures accounting for model overfitting and model performance measures, especially model calibration. Full model information was poorly reported (3/55 model developments), specifically model intercept, baseline survival or full model code. Most publications (54/55 model developments, 28/37 external validations) were found to have high risk of bias, predominantly due to methodological issues in the PROBAST analysis domain. The identified methodological issues may affect prediction model accuracy in heterogeneous populations. Independent external validation studies in the local population and demonstration of clinical impact are essential for the clinical implementation of outcome prediction models.

Central airway squamous metaplasia following radiation therapy mimicking local tumour recurrence.

Radiation therapy can result in injury to the lung parenchyma and central airways; the latter is less well documented in the literature. Here, we describe a 65-year-old Caucasian male, who developed focal endobronchial nodules and right main bronchial stenosis suggesting tumour recurrence, 32 months following curative intent concurrent chemoradiation therapy for Stage 3B squamous cell carcinoma of the lung. Computed tomography and positron emission tomography results are detailed. Flexible bronchoscopy with bronchial biopsies revealed squamous metaplasia rather than malignant tumour recurrence, with ongoing observation planned.

Qualitative study of international key informants' perspectives on the current and future state of healthcare quality measurement and feedback.

OBJECTIVES: The aim of this study is to explore the current and future state of quality measurement and feedback and identify factors influencing measurement feedback systems, including the barriers and enablers to their effective design, implementation, use and translation into quality improvement. DESIGN: This qualitative study used semistructured interviews with key informants. A deductive framework analysis was conducted to code transcripts to the Theoretical Domains Framework (TDF). An inductive analysis was used to produce subthemes and belief statements within each TDF domain. SETTING: All interviews were conducted by videoconference and audio-recorded. PARTICIPANTS: Key informants were purposively sampled experts in quality measurement and feedback, including clinical (n=5), government (n=5), research (n=4) and health service leaders (n=3) from Australia (n=7), the USA (n=4), the UK (n=2), Canada (n=2) and Sweden (n=2). RESULTS: A total of 17 key informants participated in the study. The interview length ranged from 48 to 66 min. 12 theoretical domains populated by 38 subthemes were identified as relevant to measurement feedback systems. The most populous domains included environmental context and resources, memory, attention and decision-making, and social influences. The most populous subthemes included 'quality improvement culture', 'financial and human resource support' and 'patient-centred measurement'. There were minimal conflicting beliefs outside of 'data quality and completeness'. Conflicting beliefs in these subthemes were predominantly between government and clinical leaders. CONCLUSIONS: Multiple factors were found to influence measurement feedback systems and future considerations are presented within this manuscript. The barriers and enablers that impact these systems are complex. While there are some clear modifiable factors in the design of measurement and feedback processes, influential factors described by key informants were largely socioenvironmental. Evidence-based design and implementation, coupled with a deeper understanding of the implementation context, may lead to enhanced quality measurement feedback systems and ultimately improved care delivery and patient outcomes.

Central airway squamous metaplasia following radiation therapy mimicking local tumour recurrence.

Radiation therapy can result in injury to the lung parenchyma and central airways; the latter is less well documented in the literature. Here, we describe a 65-year-old Caucasian male, who developed focal endobronchial nodules and right main bronchial stenosis suggesting tumour recurrence, 32 months following curative intent concurrent chemoradiation therapy for Stage 3B squamous cell carcinoma of the lung. Computed tomography and positron emission tomography results are detailed. Flexible bronchoscopy with bronchial biopsies revealed squamous metaplasia rather than malignant tumour recurrence, with ongoing observation planned.

Patterns of curative treatment for non-small cell lung cancer in New South Wales, Australia.

INTRODUCTION: There is a lack of large population-based studies examining patterns of curative treatment for non-small cell lung cancer (NSCLC) in Australia. This study aimed to evaluate the utilization of curative treatment for NCSLC at a population level and identify factors associated with its use in New South Wales (NSW), Australia. METHODS: Patients diagnosed with localized or locoregional NSCLC between 2009 and 2014 were identified from the NSW Central Cancer Registry. Curative treatment was defined as surgery or radiotherapy with a 45 Gy minimum dose. Univariate and multivariable analyses were performed to investigate factors associated with the receipt of curative treatment. A Cox proportional-hazards regression model was used to analyze the factors associated with 2-year overall survival (OS). RESULTS: Of the 5722 patients diagnosed with NSCLC in the study period, 3355 (59%) patients received curative treatment and 2367 (41%) patients did not receive curative treatment. The receipt of curative treatment was significantly associated with younger patients, female gender, localized disease, and Charlson Comorbidity Index (CCI) = 0. The use of curative treatment increased significantly over time from 2009 (55%) to 2014 (63%) and varied significantly from 24% to 70% between local health districts (LHDs) of residence. Younger age, female gender, localized disease, CCI = 0, and overseas country of birth were significantly associated with 2-year OS. The 2-year OS significantly improved from 70% in 2009 to 77% in 2014 for patients who received curative treatment. CONCLUSION: The use of curative treatment for patients with potentially curable NSCLC was low at 59%. However, the use of curative treatment and survival have increased over time. Significant variation was noted in the use of curative treatment between LHDs.