Effect of patient choice and hospital competition on service configuration and technology adoption within cancer surgery: a national, population-based study.

BACKGROUND: There is a scarcity of evidence about the role of patient choice and hospital competition policies on surgical cancer services. Previous evidence has shown that patients are prepared to bypass their nearest cancer centre to receive surgery at more distant centres that better meet their needs. In this national, population-based study we investigated the effect of patient mobility and hospital competition on service configuration and technology adoption in the National Health Service (NHS) in England, using prostate cancer surgery as a model. METHODS: We mapped all patients in England who underwent radical prostatectomy between Jan 1, 2010, and Dec 31, 2014, according to place of residence and treatment location. For each radical prostatectomy centre we analysed the effect of hospital competition (measured by use of a spatial competition index [SCI], with a score of 0 indicating weakest competition and 1 indicating strongest competition) and the effect of being an established robotic radical prostatectomy centre at the start of 2010 on net gains or losses of patients (difference between number of patients treated in a centre and number expected based on their residence), and the likelihood of closing their radical prostatectomy service. FINDINGS: Between Jan 1, 2010, and Dec 31, 2014, 19 256 patients underwent radical prostatectomy at an NHS provider in England. Of the 65 radical prostatectomy centres open at the start of the study period, 23 (35%) had a statistically significant net gain of patients during 2010-14. Ten (40%) of these 23 were established robotic centres. 37 (57%) of the 65 centres had a significant net loss of patients, of which two (5%) were established robotic centres and ten (27%) closed their radical prostatectomy service during the study period. Radical prostatectomy centres that closed were more likely to be located in areas with stronger competition (highest SCI quartile [0·87-0·92]; p=0·0081) than in areas with weaker competition. No robotic surgery centre closed irrespective of the size of net losses of patients. The number of centres performing robotic surgery increased from 12 (18%) of the 65 centres at the beginning of 2010 to 39 (71%) of 55 centres open at the end of 2014. INTERPRETATION: Competitive factors, in addition to policies advocating centralisation and the requirement to do minimum numbers of surgical procedures, have contributed to large-scale investment in equipment for robotic surgery without evidence of superior outcomes and contributed to the closure of cancer surgery units. If quality performance and outcome indicators are not available to guide patient choice, these policies could threaten health services' ability to deliver equitable and affordable cancer care. FUNDING: National Institute for Health Research

The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study.

BACKGROUND: Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types. METHODS: In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15-84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data. FINDINGS: We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9-9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266-295) and 344 (329-358) additional deaths. For colorectal cancer, we estimate 1445 (1392-1591) to 1563 (1534-1592) additional deaths, a 15·3-16·6% increase; for lung cancer, 1235 (1220-1254) to 1372 (1343-1401) additional deaths, a 4·8-5·3% increase; and for oesophageal cancer, 330 (324-335) to 342 (336-348) additional deaths, 5·8-6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291-3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204-63 229 years. INTERPRETATION: Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer. FUNDING: UK Research and Innovation Economic and Social Research Council

A metadata approach for clinical data management in translational genomics studies in breast cancer.

BACKGROUND: In molecular profiling studies of cancer patients, experimental and clinical data are combined in order to understand the clinical heterogeneity of the disease: clinical information for each subject needs to be linked to tumour samples, macromolecules extracted, and experimental results. This may involve the integration of clinical data sets from several different sources: these data sets may employ different data definitions and some may be incomplete. METHODS: In this work we employ semantic web techniques developed within the CancerGrid project, in particular the use of metadata elements and logic-based inference to annotate heterogeneous clinical information, integrate and query it. RESULTS: We show how this integration can be achieved automatically, following the declaration of appropriate metadata elements for each clinical data set; we demonstrate the practicality of this approach through application to experimental results and clinical data from five hospitals in the UK and Canada, undertaken as part of the METABRIC project (Molecular Taxonomy of Breast Cancer International Consortium). CONCLUSION: We describe a metadata approach for managing similarities and differences in clinical datasets in a standardized way that uses Common Data Elements (CDEs). We apply and evaluate the approach by integrating the five different clinical datasets of METABRIC.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

DART: Denoising Algorithm based on Relevance network Topology improves molecular pathway activity inference

Abstract Background Inferring molecular pathway activity is an important step towards reducing the complexity of genomic data, understanding the heterogeneity in clinical outcome, and obtaining molecular correlates of cancer imaging traits. Increasingly, approaches towards pathway activity inference combine molecular profiles (e.g gene or protein expression) with independent and highly curated structural interaction data (e.g protein interaction networks) or more generally with prior knowledge pathway databases. However, it is unclear how best to use the pathway knowledge information in the context of molecular profiles of any given study. Results We present an algorithm called DART (Denoising Algorithm based on Relevance network Topology) which filters out noise before estimating pathway activity. Using simulated and real multidimensional cancer genomic data and by comparing DART to other algorithms which do not assess the relevance of the prior pathway information, we here demonstrate that substantial improvement in pathway activity predictions can be made if prior pathway information is denoised before predictions are made. We also show that genes encoding hubs in expression correlation networks represent more reliable markers of pathway activity. Using the Netpath resource of signalling pathways in the context of breast cancer gene expression data we further demonstrate that DART leads to more robust inferences about pathway activity correlations. Finally, we show that DART identifies a hypothesized association between oestrogen signalling and mammographic density in ER+ breast cancer. Conclusions Evaluating the consistency of prior information of pathway databases in molecular tumour profiles may substantially improve the subsequent inference of pathway activity in clinical tumour specimens. This de-noising strategy should be incorporated in approaches which attempt to infer pathway activity from prior pathway models. </jats:sec

Economic impact of avoidable cancer deaths caused by diagnostic delay during the COVID-19 pandemic: A national population-based modelling study in England, UK.

INTRODUCTION: Delays in cancer diagnosis arose from the commencement of non-pharmaceutical interventions (NPI) introduced in the UK in March 2020 in response to the COVID-19 pandemic. Our earlier work predicted this will lead to approximately 3620 avoidable deaths for four major tumour types (breast, bowel, lung, and oesophageal cancer) in the next 5 years. Here, using national population-based modelling, we estimate the health and economic losses resulting from these avoidable cancer deaths. We also compare these with the impact of an equivalent number of COVID-19 deaths to understand the welfare consequences of the different health conditions. METHODS: We estimate health losses using quality-adjusted life years (QALYs) and lost economic productivity using the human capital (HC) approach. The analysis uses linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15-84 years, diagnosed with breast, colorectal, and oesophageal cancer between 1st Jan to 31st Dec 2010, with follow-up data until 31st Dec 2014, and diagnosed with lung cancer between 1st Jan to 31st Dec 31 2012, with follow-up data until 31st Dec 2015. Productivity losses are based on the estimation of excess additional deaths due to cancer at 1, 3 and 5 years for the four cancer types, which were derived from a previous analysis using this dataset. A total of 500 random samples drawn from the total number of COVID-19 deaths reported by the Office for National Statistics, stratified by gender, were used to estimate productivity losses for an equivalent number of deaths (n = 3620) due to SARS-CoV-2 infection. RESULTS: We collected data for 32,583 patients with breast cancer, 24,975 with colorectal cancer, 6744 with oesophageal cancer, and 29,305 with lung cancer. We estimate that across the four site-specific cancers combined in England alone, additional excess cancer deaths would amount to a loss of 32,700 QALYs (95% CI 31,300-34,100) and productivity losses of £103.8million GBP (73.2-132.2) in the next five years. For breast cancer, we estimate a loss of 4100 QALYS (3900-4400) and productivity losses of £23.2 m (18.2-28.6); for colorectal cancer, 15,000 QALYS (14,100-16,000) lost and productivity losses of £35.7 m (22.4-48.7); for lung cancer 10,900 QALYS (9,900-11,700) lost and productivity losses of £38.3 m (14.0-59.9) for lung cancer; and for oesophageal cancer, 2700 QALYS (2300-3,100) lost and productivity losses of £6.6 m (-6 to -17.6). In comparison, the equivalent number of COVID-19 deaths caused approximately 21,450 QALYs lost, as well as productivity losses amounting to £76.4 m (73.5-79.2). CONCLUSION: Premature cancer deaths resulting from diagnostic delays during the first wave of the COVID-19 pandemic in the UK will result in significant economic losses. On a per-capita basis, this impact is, in fact, greater than that of deaths directly attributable to COVID-19. These results emphasise the importance of robust evaluation of the trade-offs of the wider health, welfare and economic effects of NPI to support both resource allocation and the prioritisation of time-critical health services directly impacted in a pandemic, such as cancer care

Association of travel time, patient characteristics, and hospital quality with patient mobility for breast cancer surgery: A national population-based study

BACKGROUND: This national study investigated hospital quality and patient factors associated with treatment location for breast cancer surgery. METHODS: By using linked administrative data sets from the English National Health Service, the authors identified all women diagnosed between January 2, 2016, and December 31, 2018, who underwent breast-conserving surgery (BCS) or a mastectomy with or without immediate breast reconstruction. The extent to which patients bypassed their nearest hospital was investigated using a geographic information system (ArcGIS). Conditional logistic regressions were used to estimate the impact of travel time, hospital quality, and patient characteristics. RESULTS: 22,622 Of 69,153 patients undergoing BCS, 22,622 (32.7%) bypassed their nearest hospital; and, of 23,536 patients undergoing mastectomy, 7179 (30.5%) bypassed their nearest hospital. Women who were younger, without comorbidities, or from rural areas were more likely to travel to more distant hospitals (p < .05). Patients undergoing BCS (odds ratio [OR], 1.85; 95% confidence interval [CI], 1.36-2.50) or mastectomy (OR, 1.52; 95% CI, 1.14-2.02) were more likely to be treated at specialist breast reconstruction centers despite not undergoing the procedure. Patients receiving mastectomy and immediate breast reconstruction were more likely to travel to hospitals employing surgeons who had a media reputation (OR, 2.41; 95% CI, 1.28-4.52). Patients undergoing BCS were less likely to travel to hospitals with shorter surgical waiting times (OR, 0.65; 95% CI, 0.46-0.92). The authors did not observe a significant impact for research activity, hospital quality rating, breast re-excision rates, or the status as a multidisciplinary cancer center. CONCLUSIONS: Patient choice policies may drive inequalities in the health care system without improving patient outcomes

The impact of national non-pharmaceutical interventions ('lockdowns') on the presentation of cancer patients.

One of the most ignored aspects of the COVID-19 pandemic has been the impact of public health measures by governments on wider health and welfare. From March 2020, hospitals in the UK saw a dramatic reduction in patients with cancer presenting due to multifactorial reasons. The impact of the pandemic on patients with cancer in the South East London Cancer Alliance was studied. The specific aims were (1) to examine the reduction in cancer diagnoses during the first wave of the pandemic and (2) to examine the stage of diagnosis of patients with cancer presenting during the pandemic compared with that of patients presenting before the pandemic. There was an 18.2% reduction in new cancer diagnoses (an estimate of 987 cancers), when compared with 2019. This fall in cancer diagnoses was most marked in patients with prostate (51.4%), gynaecological (29.7%), breast (29.5%) and lung (23.4%) cancers. There was an overall 3.9% increase in advanced stage presentation (Stages 3 and 4), with an overall 6.8% increase in Stage 4 cancers during this period. The greatest shifts were seen in lung (increase of 6.3%, with an 11.2% increase in Stage 4 cancer alone) and colorectal (5.4%) cancers. For prostate cancer, there was an increase in 3.8% in those presenting with Stage 4 disease. For breast cancer, there was an 8% reduction in patients diagnosed with Stage 1 cancer with commensurate increases in the proportion of those with Stage 2 disease. The experiences in cancer are a salient warning that pandemic control measures and policy need to balance all health and welfare. Alternative strategies need to be adopted during further waves of the current and any future pandemic to ensure that patients with cancer are prioritised for diagnosis and treatment to prevent late-stage presentation and an increase in avoidable deaths

Association between COVID-19 burden and delays to diagnosis and treatment of cancer patients in England

BACKGROUND: The COVID-19 pandemic has been highly disruptive for cancer care. Here, we examined the effect COVID-19 had on performance of the 62-day Cancer Waiting Time (CWT) target set by the National Health Service (NHS) in England. METHODS: Data were retrospectively obtained on COVID-19 hospitalisations and CWT for NHS hospitals in England (n = 121). We produced a 'COVID-19 burden' to describe the proportion of each provider's beds occupied with COVID-19 patients. COVID-19 burden was examined against CWT performance for 1st April - 30th May 2020 (Wave 1), and 1st October - 30th November 2020 (Wave 2). Two-tailed Spearman correlations were used to identify relationships between COVID-19 burden and CWT performance amongst different referral (i.e., 2-week-wait (2 W W) and internal specialist) and tumour types. Significantly correlated variables were further examined using linear regression models. RESULTS: COVID-19 burden was negatively associated with the percentage of 2 W W pathway referrals that met the CWT target in Wave 1 (r= -0.30, p = 0.001) and Wave 2 (r= -0.21, p = 0.02). These associations were supported by the results from our linear regression models (B for wave 1: -0.71; 95 %CI: -1.03 to -0.40; B for wave 2: -0.38; 95 %CI: -0.68 to -0.07). No associations were found between COVID-19 burden and internal specialist referrals or tumour type. CONCLUSION: Increased COVID-19 burden was associated with lower compliance with CWT targets amongst urgent referrals from primary care in England. This will likely be an ongoing issue due to the backlog of patients awaiting investigations and treatment. POLICY SUMMARY: As the number of cancer referrals improve, we highlight the need for changes to primary and secondary care to manage the backlog within cancer diagnostic services to alleviate the impact of COVID-19

Constitutively Enhanced Lymphatic Pumping in the Upper Limbs of Women Who Later Develop Breast Cancer-Related Lymphedema.

BACKGROUND: It has previously been shown that the lymph drainage rate in both upper limbs is greater in women destined to develop breast cancer-related lymphedema (BCRL) than in those who do not develop BCRL, indicating a constitutive predisposition. We explored constitutive differences further by measuring the maximum lymphatic pump pressure (Ppump) and the rate of (99m)Tc-Nanocoll transport generated by the contractile upper limb lymphatics before and after breast cancer surgery in a group of women who were followed for 2 years to determine their eventual BCRL or non-BCRL status. METHODS AND RESULTS: Ppump and tracer transport rate were measured by lymphatic congestion lymphoscintigraphy in the ipsilateral upper limb in 26 women pre- and post-breast cancer surgery. BCRL occurred in 10/26 (38.5%) cases. Ppump in the women who later developed BCRL (40.0 ± 8.2 mmHg) was 1.7-fold higher than in those who did not develop BCRL (23.1 ± 10.8 mmHg, p = 0.001). Moreover, the rate of lymph tracer transport into the forearm was 2.2-fold greater in the women who later developed BCRL (p = 0.052). Surgery did not significantly reduce Ppump measured 21 weeks postsurgery, but impaired forearm tracer transport in pre-BCRL women by 58% (p = 0.047), although not in those who did not develop BCRL. CONCLUSIONS: Women destined to develop BCRL have higher pumping pressures and lymph transport, indicating harder-working lymphatics before cancer treatment. Axillary lymphatic damage from surgery appears to compromise lymph drainage in those women constitutively predisposed to higher lymphatic pressures and lymph transport