Early cancer diagnosis: reaching targets across whole populations amidst setbacks

StellarPath: Hierarchical-vertical multi-omics classifier synergizes stable markers and interpretable similarity networks for patient profiling

The Patient Similarity Network paradigm implies modeling the similarity between patients based on specific data. The similarity can summarize patients' relationships from high-dimensional data, such as biological omics. The end PSN can undergo un/supervised learning tasks while being strongly interpretable, tailored for precision medicine, and ready to be analyzed with graph-theory methods. However, these benefits are not guaranteed and depend on the granularity of the summarized data, the clarity of the similarity measure, the complexity of the network's topology, and the implemented methods for analysis. To date, no patient classifier fully leverages the paradigm's inherent benefits. PSNs remain complex, unexploited, and meaningless. We present StellarPath, a hierarchical-vertical patient classifier that leverages pathway analysis and patient similarity concepts to find meaningful features for both classes and individuals. StellarPath processes omics data, hierarchically integrates them into pathways, and uses a novel similarity to measure how patients' pathway activity is alike. It selects biologically relevant molecules, pathways, and networks, considering molecule stability and topology. A graph convolutional neural network then predicts unknown patients based on known cases. StellarPath excels in classification performances and computational resources across sixteen datasets. It demonstrates proficiency in inferring the class of new patients described in external independent studies, following its initial training and testing phases on a local dataset. It advances the PSN paradigm and provides new markers, insights, and tools for in-depth patient profiling.

Where are the inequalities in ovarian cancer care in a country with universal healthcare? A systematic review and narrative synthesis

INTRODUCTION

Patients diagnosed with ovarian cancer from more deprived areas may face barriers to accessing timely, quality healthcare. We evaluated the literature for any association between socioeconomic group, treatments received and hospital delay among patients diagnosed with ovarian cancer in the United Kingdom, a country with universal healthcare.

METHODS

We searched MEDLINE, EMBASE, CINAHL, CENTRAL, SCIE, AMED, PsycINFO and HMIC from inception to January 2023. Forward and backward citation searches were conducted. Two reviewers independently reviewed titles, abstracts, and full-text articles. UK-based studies were included if they reported socioeconomic measures and an association with either treatments received or hospital delay. The inclusion of studies from one country ensured greater comparability. Risk of bias was assessed using the QUIPS tool, and a narrative synthesis was conducted. The review is reported to PRISMA 2020 and registered with PROSPERO [CRD42022332071].

RESULTS

Out of 2876 references screened, ten were included. Eight studies evaluated treatments received, and two evaluated hospital delays. We consistently observed socioeconomic inequalities in the likelihood of surgery (range of odds ratios 0.24-0.99) and chemotherapy (range of odds ratios 0.70-0.99) among patients from the most, compared with the least, deprived areas. There were no associations between socioeconomic groups and hospital delay.

POLICY SUMMARY

Ovarian cancer treatments differed between socioeconomic groups despite the availability of universal healthcare. Further research is needed to understand why, though suggested reasons include patient choice, health literacy, and financial and employment factors. Qualitative research would provide a rich understanding of the complex factors that drive these inequalities.

The prevalence and correlates of comorbidities among patients with cancer attending a tertiary care cancer center in South India: An analytical cross-sectional study

Background

Comorbidities in patients with cancer can affect treatment, and should, therefore, be prioritized and managed.

Objectives

Our primary aim was to assess the prevalence of comorbidities among patients with cancer. The secondary objective was to identify the association of comorbidities with various sociodemographic and clinical variables.

Materials and Methods

This was a cross-sectional study conducted between December 2019 and March 2020 among patients with cancer, seeking treatment at Malabar Cancer Center, in Kannur District of northern Kerala in South India. Semi-structured interviews were conducted, and comorbidities were assessed using the Charlson Comorbidity Index. The anthropometric measurements were recorded using a standardized instrument and protocol.

Results

We enrolled 242 patients in this study. There were 148 (61.2%) female patients; 106 (43.8%) were aged between 41 and 50 years. Cancers of the head-and-neck and breast accounted for the majority of cases (23.1% each, n = 56), followed by the digestive system (18.6%, n = 45) and female reproductive system (11.2%, n = 27). The most common primary cancers in the head-and-neck, digestive, and female reproductive systems were oral, colorectal, and cervical, respectively. The prevalence of comorbidities among patients with cancer was 70.2% (n = 170). Common comorbidities were hypertension (n = 82 ; 33.9%), arthritis (n = 57; 23.6%), and diabetes (n = 53; 21.6%). After controlling for potential confounders, the factors noted to be independently associated with the presence of comorbidities were advanced age, family history of comorbidity, normal weight or underweight, and cancer treatment for more than 6 months' duration.

Conclusions

The high prevalence of comorbidities among patients with cancer suggests the need for an integrated system of care and management as the comorbidities affect the overall management of cancer treatment and care.

Assessment of patients' preferences for new anticancer drugs in China: a best-worst discrete choice experiment on three common cancer types

OBJECTIVES

Despite the advancement in anticancer drug therapies, cancer treatment decisions are often complex and preference-sensitive, making them well suited for studying shared decision-making (SDM). Our study aimed to assess preferences for new anticancer drugs among three common types of patients with cancer to inform SDM.

DESIGN

We identified five attributes of new anticancer drugs and used a Bayesian-efficient design to generate choice sets for a best-worst discrete choice experiment (BWDCE). The mixed logit regression model was applied to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity.

SETTING

The BWDCE was conducted in Jiangsu province and Hebei province in China.

PARTICIPANTS

Patients aged 18 years or older, who had a definite diagnosis of lung cancer, breast cancer or colorectal cancer were recruited.

RESULTS

Data from 468 patients were available for analysis. On average, the most valued attribute was the improvement in health-related quality of life (HRQoL) (p<0.001). The low incidence of severe to life-threatening side effects, prolonged progression-free survival and the low incidence of mild to moderate side effects were also positive predictors of patients' preferences (p<0.001). Out-of-pocket cost was a negative predictor of their preferences (p<0.001). According to subgroup analysis by type of cancer, the improvement in HRQoL remained the most valuable attribute. However, the relative importance of other attributes varied by type of cancer. Whether patients were newly diagnosed or previously diagnosed cancer cases played a dominant role in the preference heterogeneity within each subgroup.

CONCLUSIONS

Our study can assist in the implementation of SDM by providing evidence on patients' preferences for new anticancer drugs. Patients should be informed of the multiattribute values of new drugs and encouraged to make decisions reflecting their values.

Circulating tumour cells for early detection of clinically relevant cancer

Given that cancer mortality is usually a result of late diagnosis, efforts in the field of early detection are paramount to reducing cancer-related deaths and improving patient outcomes. Increasing evidence indicates that metastasis is an early event in patients with aggressive cancers, often occurring even before primary lesions are clinically detectable. Metastases are usually formed from cancer cells that spread to distant non-malignant tissues via the blood circulation, termed circulating tumour cells (CTCs). CTCs have been detected in patients with early stage cancers and, owing to their association with metastasis, might indicate the presence of aggressive disease, thus providing a possible means to expedite diagnosis and treatment initiation for such patients while avoiding overdiagnosis and overtreatment of those with slow-growing, indolent tumours. The utility of CTCs as an early diagnostic tool has been investigated, although further improvements in the efficiency of CTC detection are required. In this Perspective, we discuss the clinical significance of early haematogenous dissemination of cancer cells, the potential of CTCs to facilitate early detection of clinically relevant cancers, and the technological advances that might improve CTC capture and, thus, diagnostic performance in this setting.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Beyond glyco-proteomics-Understanding the role of genetics in cancer biomarkers

The development of robust cancer biomarkers is the most effective way to improve overall survival, as early detection and treatment leads to significantly better clinical outcomes. Many of the cancer biomarkers that have been identified and are clinically utilized are glycoproteins, oftentimes a specific glycoform. Aberrant glycosylation is a common theme in cancer, with dysregulated glycosylation driving tumor initiation and metastasis, and abnormal glycosylation can be detection both on the tissue surface and in serum. However, most cancer types are heterogeneous in regard to tumor genomics, and this heterogeneity extends to cancer glycomics. This limits the sensitivity of standalone glycan-based biomarkers, which has slowed their implementation clinically. However, if targeted biomarker development can take into account genomic tumor information, the development of complementary biomarkers that target unique cancer subgroups can be accomplished. This idea suggests the need for algorithm-based cancer biomarkers, which can utilize multiple biomarkers along with relevant demographic information. This concept has already been established in the detection of hepatocellular carcinoma with the GALAD score, and an algorithm-based approach would likely be effective in improving biomarker sensitivity for additional cancer types. In order to increase cancer diagnostic biomarker sensitivity, there must be more targeted biomarker development that considers tumor genomic, proteomic, metabolomic, and clinical data while identifying tumor biomarkers.

Housing Insecurity Among Patients With Cancer

Social determinants of health are the economic and environmental conditions under which people are born, live, work, and age that affect health. These structural factors underlie many of the long-standing inequities in cancer care and outcomes that vary by geography, socioeconomic status, and race and ethnicity in the United States. Housing insecurity, including lack of safe, affordable, and stable housing, is a key social determinant of health that can influence-and be influenced by-cancer care across the continuum, from prevention to screening, diagnosis, treatment, and survivorship. During 2021, the National Cancer Policy Forum of the National Academies of Science, Engineering, and Medicine sponsored a series of webinars addressing social determinants of health, including food, housing, and transportation insecurity, and their associations with cancer care and patient outcomes. This dissemination commentary summarizes the formal presentations and panel discussions from the webinar devoted to housing insecurity. It provides an overview of housing insecurity and health care across the cancer control continuum, describes health system interventions to minimize the impact of housing insecurity on patients with cancer, and identifies challenges and opportunities for addressing housing insecurity and improving health equity. Systematically identifying and addressing housing insecurity to ensure equitable access to cancer care and reduce health disparities will require ongoing investment at the practice, systems, and broader policy levels.

Being sick to a cancer patient: pathways of delay in help seeking and diagnosis of cancer in India

There is evidence that cancer mortality and morbidity could be reduced when the disease is diagnosed and treated at an early stage. The paper examines the pathways of delay of cancer diagnosis in an Indian setting. It draws on a qualitative study conducted among cancer survivors and family members of cancer patients in the city of Bengaluru, South India. The results show that a substantial part of the delay occurred at the stage of initial formal help seeking wherein patient and family-led, disease-related and systemic factors together played a major role. Patient-led factors included trivialisation and normalisation of symptoms as part of general fatigue and aging; unrealistic risk perceptions that linked causality of cancer merely to heredity and behavioural risk factors; fear of being diagnosed as cancer patient; gender related reasons including family's gender performance expectation, lower agency of women to seek help and lower prioratisation of women's health in the household and access related issues including financial constraints and unavailability of specialised hospitals nearby. Disease-related factors included the presence of comorbidity, cancer's mimicking of symptoms of other diseases and absence of distinguishable symptoms at the initial stage for certain types of cancers. The practitioner-led and system-led factors such as trivialisation of symptoms by general practitioners, non cancer-specific referrals, and lack of cancer screening facilities accounted for a major part of delay after the formal help seeking. The paper argues that the mere knowledge of cancer symptoms did not always lead to early diagnosis due to the interplay of these factors. The ongoing cancer prevention and control interventions in India need to be informed of these micro level factors while developing strategies to prevent avoidable delays in cancer diagnosis.

Head and neck cancer in the UK: what was the stage before COVID-19? UK cancer registries analysis (2011-2018)

Introduction People who present with more advanced stage head and neck cancer (HNC) are associated with poorer outcomes and survival. The burden and trends of advanced stage HNC are not fully known at the population level. The UK national cancer registries routinely collect data on HNC diagnoses.Aims To describe trends in stage of diagnosis of HNCs across the UK before the COVID-19 pandemic.Methods Aggregated HNC incidence data were requested from the national cancer registries of the four UK countries for the ten most recent years of available data by subsite and American Joint Commission on Cancer stage at diagnosis classification. Additionally, data for Scotland were available by age group, sex and area-based socioeconomic deprivation category.Results Across the UK, rates of advanced stage HNC had increased, with 59% of patients having advanced disease at diagnosis from 2016-2018. England had a lower proportion of advanced disease (58%) than Scotland, Wales or Northern Ireland (65-69%) where stage data were available. The completeness of stage data had improved over recent years (87% by 2018).Conclusion Prior to the COVID-19 pandemic, diagnoses of HNC at an advanced stage comprised the majority of HNCs in the UK, representing the major challenge for the cancer healthcare system.

Detection of Pancreatic Cancer miRNA with Biocompatible Nitrogen-Doped Graphene Quantum Dots

Early-stage pancreatic cancer remains challenging to detect, leading to a poor five-year patient survival rate. This obstacle necessitates the development of early detection approaches based on novel technologies and materials. In this work, the presence of a specific pancreatic cancer-derived miRNA (pre-miR-132) is detected using the fluorescence properties of biocompatible nitrogen-doped graphene quantum dots (NGQDs) synthesized using a bottom-up approach from a single glucosamine precursor. The sensor platform is comprised of slightly positively charged (1.14 ± 0.36 mV) NGQDs bound via π-π stacking and/or electrostatic interactions to the negatively charged (-22.4 ± 6.00 mV) bait ssDNA; together, they form a complex with a 20 nm average size. The NGQDs' fluorescence distinguishes specific single-stranded DNA sequences due to bait-target complementarity, discriminating them from random control sequences with sensitivity in the micromolar range. Furthermore, this targetability can also detect the stem and loop portions of pre-miR-132, adding to the practicality of the biosensor. This non-invasive approach allows cancer-specific miRNA detection to facilitate early diagnosis of various forms of cancer.

Sinapic acid inhibits pancreatic cancer proliferation, migration, and invasion via downregulation of the AKT/Gsk-3β signal pathway

Among digestive system cancers, the extremely poor prognosis of pancreatic cancer (PC) is a pressing concern. Nonoperative treatments such as targeted and immunotherapy, have improved the current situation, however, the accompanying side effects of these chemicals should not be ignored. Here, we discovered a novel hydroxycinnamic acid named sinapic acid (SA) derived from fruits, vegetables, cereals, and oil crops as an effective anti-PC molecule. Both the in vitro and in vivo models we designed showed that SA exhibited anticancer activities but not apoptosis induction. Research on the underlying mechanisms illustrated that AKT phosphorylation was blocked by SA, and the downstream Gsk-3β was downregulated subsequently. Our study revealed the inhibitory activity and underlying mechanisms of SA, providing evidence that SA is a potential strategy for cancer research and can be a promising option of PC chemotherapy.

Biocompatible Probes Based on Rare-Earth Doped Strontium Aluminates with Long-Lasting Phosphorescent Properties for In Vitro Optical IMAGING

In recent decades, the demand for biomedical imaging tools has grown very rapidly as a key feature for biomedical research and diagnostic applications. Particularly, fluorescence imaging has gained increased attention as a non-invasive, inexpensive technique that allows real-time imaging. However, tissue auto-fluorescence under external illumination, together with a weak tissue penetration of low wavelength excitation light, largely restricts the application of the technique. Accordingly, new types of fluorescent labels are currently being investigated and, in this search, phosphorescent nanoparticles promise great potential, as they combine the interesting size-dependent properties of nanoscale materials with a long-lasting phosphorescence-type emission that allows optical imaging well after excitation (so avoiding autofluorescence). In this work, core-shell structures consisting of SrAlO:Eu,Dy luminescent cores encapsulated within a biocompatible silica shell were prepared, showing a green persistent phosphorescence with an afterglow time of more than 1000 s. A high-energy ball milling procedure was used to reduce the size of the starting phosphors to a size suitable for cellular uptake, while the silica coating was produced by a reverse micelle methodology that eventually allows the excitation and emission light to pass efficiently through the shell. Confocal fluorescence microscopy using HeLa cancer cells confirmed the potential of the all-ceramic composites produced as feasible labels for in vitro optical imaging.

REASSURED Multiplex Diagnostics: A Critical Review and Forecast

The diagnosis of infectious diseases is ineffective when the diagnostic test does not meet one or more of the necessary standards of affordability, accessibility, and accuracy. The World Health Organization further clarifies these standards with a set of criteria that has the acronym ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free and Deliverable to end-users). The advancement of the digital age has led to a revision of the ASSURED criteria to REASSURED: Real-time connectivity, Ease of specimen collection, Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free or simple, and Deliverable to end-users. Many diagnostic tests have been developed that aim to satisfy the REASSURED criteria; however, most of them only detect a single target. With the progression of syndromic infections, coinfections and the current antimicrobial resistance challenges, the need for multiplexed diagnostics is now more important than ever. This review summarizes current diagnostic technologies for multiplexed detection and forecasts which methods have promise for detecting multiple targets and meeting all REASSURED criteria.

Did the COVID-19 Pandemic Truly Adversely Affect Disease Progress and Therapeutic Options in Breast Cancer Patients? A Single-Centre Analysis

Purpose: The uncontrolled spread and transmission of SARS-CoV-2 infections has disrupted most areas of social and economic life all over the world. The most important changes concern problems related to the functioning of healthcare systems. The aim of this study was to evaluate clinical consequences associated with the COVID-19 pandemic for patients with newly diagnosed breast cancer, treated at our centre. Methods: The study participants were patients first time diagnosed with breast cancer, treated between January 2019 and March 2021, who were provided any type of cancer treatment at our centre. The study determined the grade of clinical and pathological progress of the disease and types of cancer treatment applied in patients. Results: In total, 2863 patients were included in the analysis. The number of hospitalized patients was 1228 (1123 treated surgically, 105 receiving conservative treatment) in 2019, 1318 (1206 and 112 patients, respectively) in 2020, and 317 (288 and 29 patients, respectively) in 2021. Conclusions: Despite many hazards associated with the new epidemiological situation, we were able to maintain the continuous operation of our centre. We have achieved a measurable success, and even managed to increase the number of treated breast cancer patients.

Graphene Quantum Dots prepared by Electron Beam Irradiation for Safe Fluorescence Imaging of Tumor

Graphene quantum dots (GQD) have attracted much attention due to their unique properties in biomedical application, such as biosensing, imaging, and drug delivering. However, scale preparing red luminescing GQD is still challenging now. Herein, with the help of electron beam irradiation, a simple, rapid, and efficient up-to-down strategy was developed to synthesize GQD with size of 2.75 nm emitting 610 nm luminescence. GQD were further functionalized with polyethylene glycol (PEG) and exhibited good solubility and biocompatibility. The potential in vivo toxicity of PEGylated GQD could completely be eliminated by the clinic cholesterol-lowering drug simvastatin. PEGylated GQD could selectively accumulate in tumor after intravenous injection as a security, reliable and sensitive tumor fluorescence imaging agent. Therefore, this work presented a new method preparing red luminescing GQD for biomedical application.

A Comprehensive Updated Review on Magnetic Nanoparticles in Diagnostics

Magnetic nanoparticles (MNPs) have been studied for diagnostic purposes for decades. Their high surface-to-volume ratio, dispersibility, ability to interact with various molecules and superparamagnetic properties are at the core of what makes MNPs so promising. They have been applied in a multitude of areas in medicine, particularly Magnetic Resonance Imaging (MRI). Iron oxide nanoparticles (IONPs) are the most well-accepted based on their excellent superparamagnetic properties and low toxicity. Nevertheless, IONPs are facing many challenges that make their entry into the market difficult. To overcome these challenges, research has focused on developing MNPs with better safety profiles and enhanced magnetic properties. One particularly important strategy includes doping MNPs (particularly IONPs) with other metallic elements, such as cobalt (Co) and manganese (Mn), to reduce the iron (Fe) content released into the body resulting in the creation of multimodal nanoparticles with unique properties. Another approach includes the development of MNPs using other metals besides Fe, that possess great magnetic or other imaging properties. The future of this field seems to be the production of MNPs which can be used as multipurpose platforms that can combine different uses of MRI or different imaging techniques to design more effective and complete diagnostic tests.

Current and Future Advancements of Raman Spectroscopy Techniques in Cancer Nanomedicine

Raman scattering is one of the most used spectroscopy and imaging techniques in cancer nanomedicine due to its high spatial resolution, high chemical specificity, and multiplexity modalities. The flexibility of Raman techniques has led, in the past few years, to the rapid development of Raman spectroscopy and imaging for nanodiagnostics, nanotherapy, and nanotheranostics. This review focuses on the applications of spontaneous Raman spectroscopy and bioimaging to cancer nanotheranostics and their coupling to a variety of diagnostic/therapy methods to create nanoparticle-free theranostic systems for cancer diagnostics and therapy. Recent implementations of confocal Raman spectroscopy that led to the development of platforms for monitoring the therapeutic effects of anticancer drugs in vitro and in vivo are also reviewed. Another Raman technique that is largely employed in cancer nanomedicine, due to its ability to enhance the Raman signal, is surface-enhanced Raman spectroscopy (SERS). This review also explores the applications of the different types of SERS, such as SERRS and SORS, to cancer diagnosis through SERS nanoprobes and the detection of small-size biomarkers, such as exosomes. SERS cancer immunotherapy and immuno-SERS (iSERS) microscopy are reviewed.

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.