BACKGROUND: Distal radius (wrist) fractures are the second most common fracture admitted to hospital. The anatomical pattern of these types of injuries is diverse, with variation in clinical management, guidelines for management remain inconclusive, and the uptake of findings from clinical trials into routine practice limited. Robust predictive modelling, which considers both the characteristics of the fracture and patient, provides the best opportunity to reduce variation in care and improve patient outcomes. This type of data is housed in unstructured data sources with no particular format or schema. The "Predicting fracture outcomes from clinical Registry data using Artificial Intelligence (AI) Supplemented models for Evidence-informed treatment (PRAISE)" study aims to use AI methods on unstructured data to describe the fracture characteristics and test if using this information improves identification of key fracture characteristics and prediction of patient-reported outcome measures and clinical outcomes following wrist fractures compared to prediction models based on standard registry data. METHODS AND DESIGN: Adult (16+ years) patients presenting to the emergency department, treated in a short stay unit, or admitted to hospital for >24h for management of a wrist fracture in four Victorian hospitals will be included in this study. The study will use routine registry data from the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR), and electronic medical record (EMR) information (e.g. X-rays, surgical reports, radiology reports, images). A multimodal deep learning fracture reasoning system (DLFRS) will be developed that reasons on EMR information. Machine learning prediction models will test the performance with/without output from the DLFRS. DISCUSSION: The PRAISE study will establish the use of AI techniques to provide enhanced information about fracture characteristics in people with wrist fractures. Prediction models using AI derived characteristics are expected to provide better prediction of clinical and patient-reported outcomes following distal radius fracture.

Whilst some of the diversity in management of women with ductal carcinoma in situ (DCIS) may be explained by tumour characteristics, the role of patient preference and the factors underlying those preferences have been less frequently examined. We have used a descriptive qualitative study to explore treatment decisions for a group of Australian women diagnosed with DCIS through mammographic screening. Semi-structured telephone interviews were performed with 16 women diagnosed with DCIS between January 2012 and December 2018, recruited through the LifePool dataset (a subset of BreastScreen participants who have agreed to participate in research). Content analysis using deductive coding identified three themes: participants did not have a clear understanding of their diagnosis or prognosis; reported involvement in decision making about management varied; specific factors including the psychosexual impact of mastectomy and perceptions of radiotherapy, could act as barriers or facilitators to specific decisions about treatment. The treatment the women received was not simply determined by the characteristics of their disease. Interaction with the managing clinician was pivotal, however many other factors played a part in individual decisions. Recognising that decisions are not purely a function of disease characteristics is important for both women with DCIS and the clinicians who care for them.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies. While immortalized cancer cell lines and genetically engineered murine models have increased our understanding of PDAC tumorigenesis, they do not recapitulate inter- and intra-patient heterogeneity. PDAC patient derived organoid (PDO) biobanks have overcome this hurdle, and provide an opportunity for the high throughput screening of potential new therapies. This review provides a summary of the PDAC PDO biobanks established to date, and discusses how they have advanced our understanding of PDAC biology. Looking forward, the development of coculturing techniques for specific immune or stromal cell populations will enable a better understanding of the crosstalk that occurs within the tumor microenvironment, and the impact of this crosstalk on treatment response.

BACKGROUND: Research on the possible association between shiftwork and breast cancer is complicated because there are many different shiftwork factors, which might be involved including: light at night, phase shift, sleep disruption and changes in lifestyle factors while on shiftwork (diet, physical activity, alcohol intake and low sun exposure). METHODS: We conducted a population-based case-control study in Western Australia from 2009 to 2011 with 1205 incident breast cancer cases and 1789 frequency age-matched controls. A self-administered questionnaire was used to collect demographic, reproductive, and lifestyle factors and lifetime occupational history and a telephone interview was used to obtain further details about the shiftwork factors listed above. RESULTS: A small increase in risk was suggested for those ever doing the graveyard shift (work between midnight and 0500 hours) and breast cancer (odds ratio (OR)=1.16, 95% confidence interval (CI)=0.97-1.39). For phase shift, we found a 22% increase in breast cancer risk (OR=1.22, 95% CI=1.01-1.47) with a statistically significant dose-response relationship (P=0.04). For the other shiftwork factors, risks were marginally elevated and not statistically significant. CONCLUSION: We found some evidence that some of the factors involved in shiftwork may be associated with breast cancer but the ORs were low and there were inconsistencies in duration and dose-response relationships.

PURPOSE: Despite evidence supporting at least five years of endocrine therapy for early breast cancer, many women discontinue therapy early. We investigated the impact of initial therapy type and specific comorbidities on discontinuation of endocrine therapy in clinical practice. METHODS: We identified women in a population-based cohort with a diagnosis of early breast cancer and an incident dispensing of anastrozole, letrozole or tamoxifen from 2003-2008 (N = 1531). Pharmacy and health service data were used to determine therapy duration, treatment for pre-existing and post-initiation comorbidities (anxiety, depression, hot flashes, musculoskeletal pain, osteoporosis, vaginal atrophy), demographic and other clinical characteristics. Time to discontinuation of initial, and any, endocrine therapy was calculated. Cox regression determined the association of different characteristics on early discontinuation. RESULTS: Initial endocrine therapy continued for a median of 2.2 years and any endocrine therapy for 4.8 years. Cumulative probability of discontinuing any therapy was 17% after one year and 58% by five years. Initial tamoxifen, pre-existing musculoskeletal pain and newly-treated anxiety predicted shorter initial therapy but not discontinuation of any therapy. Early discontinuation of any therapy was associated with newly-treated hot flashes (HR = 2.1, 95% CI = 1.3-3.3), not undergoing chemotherapy (HR = 1.4, 95% CI = 1.1-1.8) and not undergoing mastectomy (HR = 1.5, 95% CI = 1.2-1.8). CONCLUSIONS: Less than half of women completed five years of endocrine therapy. Women at greatest risk of stopping any therapy early were those with newly-treated hot flashes, no initial chemotherapy, or no initial mastectomy. This suboptimal use means that the reductions in recurrence demonstrated in clinical trials may not be realised in practice.

BACKGROUND: Australian clinical guidelines recommend endocrine therapy for all women with hormone-dependent early breast cancer. Guidelines specify tamoxifen as first-line therapy for pre-menopausal women, and tamoxifen or an aromatase inhibitor (AI) for post-menopausal women depending on the risk of recurrence based on tumour characteristics including size. Therapies have different side effect profiles; therefore comorbidity may also influence choice. We examined comorbidity, and the clinical and demographic characteristics of women commencing different therapies. PATIENTS AND METHODS: We identified the first dispensing of tamoxifen, anastrozole or letrozole for women diagnosed with invasive breast cancer in the 45 and Up Study from 2004-2009 (N = 1266). Unit-level pharmacy and medical service claims, hospital, Cancer Registry, and self-reported data were linked to determine menopause status at diagnosis, tumour size, age, comorbidities, and change in subsidy restrictions. Chi-square tests and generalised regression models were used to compare the characteristics of women commencing different therapies. RESULTS: Most pre-menopausal women commenced therapy with tamoxifen (91%). Anastrozole was the predominant therapy for post-menopausal women (57%), followed by tamoxifen (28%). Women with osteoporosis were less likely to commence anastrozole compared with tamoxifen (anastrozole RR = 0.7, 95% CI = 0.5-0.9). Women with arthritis were 1.6-times more likely to commence letrozole than anastrozole (95% CI = 1.1-2.1). Tamoxifen was more often initiated in women with tumours >1 cm, who were also ≥75 years. Subsidy restriction changes were associated with substantial increases in the proportion of women commencing AIs (anastrozole RR = 4.3, letrozole RR = 8.3). CONCLUSIONS: The findings indicate interplay of comorbidity and therapy choice for women with invasive breast cancer. Most post-menopausal women commenced therapy with anastrozole; however, letrozole and tamoxifen were more often initiated for women with comorbid arthritis and osteoporosis, respectively. Tamoxifen was also more common for women with tumours >1 cm and aged ≥75 years. Subsidy restrictions appear to have strongly influenced therapy choice.

BACKGROUND: Statutory State-based cancer registries are considered the 'gold standard' for researchers identifying cancer cases in Australia, but research using self-report or administrative health datasets (e.g. hospital records) may not have linkage to a Cancer Registry and need to identify cases. This study investigated the validity of administrative and self-reported data compared with records in a State-wide Cancer Registry in identifying invasive breast cancer cases. METHODS: Cases of invasive breast cancer recorded on the New South Wales (NSW) Cancer Registry between July 2004 and December 2008 (the study period) were identified for women in the 45 and Up Study. Registry cases were separately compared with suspected cases ascertained from: i) administrative hospital separations records; ii) outpatient medical service claims; iii) prescription medicines claims; and iv) the 45 and Up Study baseline survey. Ascertainment flags included diagnosis codes, surgeries (e.g. lumpectomy), services (e.g. radiotherapy), and medicines used for breast cancer, as well as self-reported diagnosis. Positive predictive value (PPV), sensitivity and specificity were calculated for flags within individual datasets, and for combinations of flags across multiple datasets. RESULTS: Of 143,010 women in the 45 and Up Study, 2039 (1.4%) had an invasive breast tumour recorded on the NSW Cancer Registry during the study period. All of the breast cancer flags examined had high specificity (>97.5%). Of the flags from individual datasets, hospital-derived 'lumpectomy and diagnosis of invasive breast cancer' and '(lumpectomy or mastectomy) and diagnosis of invasive breast cancer' had the greatest PPV (89% and 88%, respectively); the later having greater sensitivity (59% and 82%, respectively). The flag with the highest sensitivity and PPV ≥ 85% was 'diagnosis of invasive breast cancer' (both 86%). Self-reported breast cancer diagnosis had a PPV of 50% and sensitivity of 85%, and breast radiotherapy had a PPV of 73% and a sensitivity of 58% compared with Cancer Registry records. The combination of flags with the greatest PPV and sensitivity was '(lumpectomy or mastectomy) and (diagnosis of invasive breast cancer or breast radiotherapy)' (PPV and sensitivity 83%). CONCLUSIONS: In the absence of Cancer Registry data, administrative and self-reported data can be used to accurately identify cases of invasive breast cancer for sample identification, removing cases from a sample, or risk adjustment. Invasive breast cancer can be accurately identified using hospital-derived diagnosis alone or in combination with surgeries and breast radiotherapy.

BACKGROUND: The germ cell supranetwork multidisciplinary team (SMDT) for the Anglian Network covers a population of 7.5 million. METHODS: We reviewed 10 years of SMDT discussion and categorised them into five domains ((1) overall outcome, (2) chemotherapy regimens-untreated disease and salvage therapy, (3) radiology, (4) pathology and (5) complex cases) to assess the impact of the SMDT. RESULTS: A total of 2892 new cases were reviewed. In the first 5 years, patients with good prognosis disease had poorer survival in low-volume vs high-volume centres (87.8 vs 95.3, p = 0.02), but the difference was no longer significant in the last 5 years (93.3 vs 95.1, p = 0.30). Radiology review of 3206 scans led to rejection of the diagnosis of progression in 26 cases and a further 10 cases were down-staged. There were 790 pathology reviews by two specialised uropathologists, which lead to changes in 75 cases. 18F-fluorodeoxyglucose (18FDG) PET-CT was undertaken during this time period but did not help to predict who would have viable cancer. A total of 26 patients with significant mental health issues who were unable to give informed consent were discussed. CONCLUSION: SMDT working has led to an improvement in outcomes and refining of treatment in patients with germ cell tumours.

[This corrects the article DOI: 10.1371/journal.pgen.1009497.].

Optical elastography is undergoing extensive development as an imaging tool to map mechanical contrast in tissue. Here, we present a new platform for optical elastography by generating sub-millimetre-scale mechanical contrast from a simple digital camera. This cost-effective, compact and easy-to-implement approach opens the possibility to greatly expand applications of optical elastography both within and beyond the field of medical imaging. Camera-based optical palpation (CBOP) utilises a digital camera to acquire photographs that quantify the light intensity transmitted through a silicone layer comprising a dense distribution of micro-pores (diameter, 30-100 µm). As the transmission of light through the micro-pores increases with compression, we deduce strain in the layer directly from intensity in the digital photograph. By pre-characterising the relationship between stress and strain of the layer, the measured strain map can be converted to an optical palpogram, a map of stress that visualises mechanical contrast in the sample. We demonstrate a spatial resolution as high as 290 µm in CBOP, comparable to that achieved using an optical coherence tomography-based implementation of optical palpation. In this paper, we describe the fabrication of the micro-porous layer and present experimental results from structured phantoms containing stiff inclusions as small as 0.5 × 0.5 × 1 mm. In each case, we demonstrate high contrast between the inclusion and the base material and validate both the contrast and spatial resolution achieved using finite element modelling. By performing CBOP on freshly excised human breast tissue, we demonstrate the capability to delineate tumour from surrounding benign tissue.

Despite the high prevalence of prostate cancer in older men, the predictive value of a polygenic risk score (PRS) remains uncertain in men aged ≥70 years. We used a 6.6 million-variant PRS to predict the risk of incident prostate cancer in a prospective study of 5701 men of European descent aged ≥70 years (mean age 75 years) enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) clinical trial. The study endpoint was prostate cancer, including metastatic or non-metastatic disease, confirmed by an expert panel. After excluding participants with a history of prostate cancer at enrolment, we used a multivariable Cox proportional hazards model to assess the association between the PRS and incident prostate cancer risk, adjusting for covariates. Additionally, we examined the distribution of Gleason grade groups by PRS group to determine if a higher PRS was associated with higher grade disease. We tested for interaction between the PRS and aspirin treatment. Logistic regression was used to independently assess the association of the PRS with prevalent (pre-trial) prostate cancer, reported in medical histories. During a median follow-up time of 4.6 years, 218 of the 5701 participants (3.8%) were diagnosed with prostate cancer. The PRS predicted incident risk with a hazard ratio (HR) of 1.52 per standard deviation (SD) (95% confidence interval (CI) 1.33-1.74, p < 0.001). Men in the top quintile of the PRS distribution had an almost three times higher risk of prostate cancer than men in the lowest quintile (HR = 2.99 (95% CI 1.90-4.27), p < 0.001). However, a higher PRS was not associated with a higher Gleason grade groups. We found no interaction between aspirin treatment and the PRS for prostate cancer risk. The PRS was also associated with prevalent prostate cancer (odds ratio = 1.80 per SD (95% CI 1.65-1.96), p < 0.001).While a PRS for prostate cancer is strongly associated with incident risk in men aged ≥70 years, the clinical utility of the PRS as a biomarker is currently limited by its inability to select for clinically significant disease.