Trends and variation in urgent referrals for suspected cancer 2009/2010-2019/2020

'ThinkCancer!': randomised feasibility trial of a novel practice-based early cancer diagnosis intervention

BACKGROUND

UK cancer deaths remain high; primary care is key for earlier cancer diagnosis as half of avoidable delays occur here. Improvement is possible through lower referral thresholds, better guideline adherence, and better safety-netting systems. Few interventions target whole practice teams. We developed a novel whole-practice team intervention to address this.

AIM

To test the feasibility and acceptability of a novel, complex behavioural intervention, 'ThinkCancer!', for assessment in a subsequent Phase III trial.

DESIGN & SETTING

Pragmatic, superiority pilot randomised controlled trial (RCT) with an embedded process evaluation and feasibility economic analysis in Welsh general practices.

METHOD

Clinical outcome data were collected from practices (the unit of randomisation). Practice characteristics and cancer safety-netting systems were assessed. Individual practice staff completed evaluation and feedback forms and qualitative interviews. The intervention was adapted and refined.

RESULTS

Trial recruitment and workshop deliveries took place between March 2020 and May 2021. Trial progression criteria for recruitment, intervention fidelity, and routine data collection were met. Staff-level fidelity, retention, and individual level data collection processes were reviewed and amended. Interviews highlighted positive participant views on all aspects of the intervention. All practices set out to liberalise referral thresholds appropriately, implement guidelines, and address safety-netting plans in detail.

CONCLUSION

'ThinkCancer!' appears feasible and acceptable. The new iteration of the workshops was completed and the Phase III trial has been funded to assess the effectiveness and cost-effectiveness of this novel professional behaviour change intervention. Delivery at scale to multiple practices will likely improve fidelity and reach.

Nomenclature of the symptoms of head and neck cancer: a systematic scoping review

Introduction

Evolution of a patient-reported symptom-based risk stratification system to redesign the suspected head and neck cancer (HNC) referral pathway (EVEREST-HN) will use a broad and open approach to the nomenclature and symptomatology. It aims to capture and utilise the patient reported symptoms in a modern way to identify patients' clinical problems more effectively and risk stratify the patient.

Method

The review followed the PRISMA checklist for scoping reviews. A search strategy was carried out using Medline, Embase and Web of Science between January 1st 2012 and October 31st 2023. All titles, abstracts and full paper were screened for eligibility, papers were assessed for inclusion using predetermined criteria. Data was extracted pertaining to the aims, type of study, cancer type, numbers of patients included and symptoms, presenting complaints or signs and symptoms.

Results

There were 9,331 publications identified in the searches, following title screening 350 abstracts were reviewed for inclusion and 120 were considered for eligibility for the review. 48 publications met the eligibility criteria and were included in the final review. Data from almost 11,000 HNC patients was included. Twenty-one of the publications were from the UK, most were retrospective examination of patient records. Data was extracted and charted according to the anatomical area of the head and neck where the symptoms are subjectively and objectively found, and presented according to lay terms for symptoms, clinical terms for symptoms and the language of objective clinical findings.

Discussion

Symptoms of HNC are common presenting complaints, interpreting these along with clinical history, examination and risk factors will inform a clinician's decision to refer as suspected cancer. UK Head and Neck specialists believe a different way of triaging the referrals is needed to assess the clinical risk of an undiagnosed HNC. EVEREST-HN aims to achieve this using the patient history of their symptoms. This review has highlighted issues in terms of what is considered a symptom, a presenting complaint and a clinical finding or sign.

The National Health Service urgent cancer referral pathway for suspected urological cancers: early economic evaluation of a risk prediction test

OBJECTIVES

In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test - the PinPoint test - to triage and prioritize patients urgently referred with suspected urological cancers.

METHODS

Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained.

RESULTS

Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain.

CONCLUSIONS

Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.

Future cancer risk after urgent suspected cancer referral in England when cancer is not found: a national cohort study

BACKGROUND

Following referral for investigation of urgent suspected cancer within the English National Health Service referral system, 7% of referred individuals are diagnosed with cancer. This study aimed to investigate the risk of cancer occurrence within 1-5 years of finding no cancer following an urgent suspected cancer referral.

METHODS

This national cohort study used urgent suspected cancer referral data for England from the Cancer Waiting Times dataset and linked it with cancer diagnosis data from the National Cancer Registration dataset. Data were extracted for the eight most commonly referred to urgent suspected cancer referral pathways (breast, gynaecological, head and neck, lower and upper gastrointestinal, lung, skin, and urological) for the period April 1, 2013, to March 31, 2014, with 5-year follow-up for individuals with no cancer diagnosis within 1 year of referral. The primary objective was to investigate the occurrence and type of subsequent cancer in years 1-5 following an urgent suspected cancer referral when no cancer was initially found, both overall and for each of the eight referral pathways. The numbers of subsequent cancers were compared with expected cancer incidence in years 1-5 following referral, using standardised incidence ratios (SIRs) based on matched age-gender distributions of expected cancer incidence in England for the same time period. The analysis was repeated, stratifying by referral group, and by calculating the absolute and expected rate of all cancers and of the same individual cancer as the initial referral.

FINDINGS

Among 1·18 million referrals without a cancer diagnosis in years 0-1, there were 63 112 subsequent cancers diagnosed 1-5 years post-referral, giving an absolute rate of 1338 (95% CI 1327-1348) cancers per 100 000 referrals per year (1038 [1027-1050] in females, 1888 [1867-1909] in males), compared with an expected rate of 1054 (1045-1064) cancers per 100 000 referrals per year (SIR 1·27 [95% CI 1·26-1·28]). The absolute rate of any subsequent cancer diagnosis 1-5 years after referral was lowest following suspected breast cancer referral (746 [728-763] cancers per 100 000 referrals per year) and highest following suspected urological (2110 [2070-2150]) or lung cancer (1835 [1767-1906]) referral. For diagnosis of the same cancer as the initial referral pathway, the highest absolute rates were for the urological and lung pathways (1011 [984-1039] and 638 [598-680] cancers per 100 000 referrals per year, respectively). The highest relative risks of subsequent diagnosis of the same cancer as the initial referral pathway were for the head and neck pathway (SIR 3·49 [95% CI 3·22-3·78]) and lung pathway (3·00 [2·82-3·20]).

INTERPRETATION

Cancer risk was higher than expected in the 5 years following an urgent suspected cancer referral. The potential for targeted interventions, such as proactive monitoring, safety-netting, and cancer awareness or risk reduction initiatives should be investigated.

FUNDING

Cancer Research UK.

Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance

Introduction

Deep Ensemble for Recognition of Malignancy (DERM) is an artificial intelligence as a medical device (AIaMD) tool for skin lesion assessment.

Methods

We report prospective real-world performance from its deployment within skin cancer pathways at two National Health Service hospitals (UK) between July 2021 and October 2022.

Results

A total of 14,500 cases were seen, including patients 18-100 years old with Fitzpatrick skin types I-VI represented. Based on 8,571 lesions assessed by DERM with confirmed outcomes, versions A and B demonstrated very high sensitivity for detecting melanoma (95.0-100.0%) or malignancy (96.0-100.0%). Benign lesion specificity was 40.7-49.4% (DERM-vA) and 70.1-73.4% (DERM-vB). DERM identified 15.0-31.0% of cases as eligible for discharge.

Discussion

We show DERM performance in-line with sensitivity targets and pre-marketing authorisation research, and it reduced the caseload for hospital specialists in two pathways. Based on our experience we offer suggestions on key elements of post-market surveillance for AIaMDs.

Progress and priorities in reducing the time to cancer diagnosis

Key developments in early diagnosis research and policy since the publication of the highly cited BJC review "Is increased time to diagnosis and treatment associated with poorer outcomes?" by Neal et al. in 2015 are summarised. Progress achieved since 2015 is described and priorities for further research identified.

Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study

OBJECTIVES

To develop and validate tests to assess the risk of any cancer for patients referred to the NHS Urgent Suspected Cancer (2-week wait, 2WW) clinical pathways.

SETTING

Primary and secondary care, one participating regional centre.

PARTICIPANTS

Retrospective analysis of data from 371 799 consecutive 2WW referrals in the Leeds region from 2011 to 2019. The development cohort was composed of 224 669 consecutive patients with an urgent suspected cancer referral in Leeds between January 2011 and December 2016. The diagnostic algorithms developed were then externally validated on a similar consecutive sample of 147 130 patients (between January 2017 and December 2019). All such patients over the age of 18 with a minimum set of blood counts and biochemistry measurements available were included in the cohort.

PRIMARY AND SECONDARY OUTCOME MEASURES

sensitivity, specificity, negative predictive value, positive predictive value, Receiver Operating Characteristic (ROC) curve Area Under Curve (AUC), calibration curves RESULTS: We present results for two clinical use-cases. In use-case 1, the algorithms identify 20% of patients who do not have cancer and may not need an urgent 2WW referral. In use-case 2, they identify 90% of cancer cases with a high probability of cancer that could be prioritised for review.

CONCLUSIONS

Combining a panel of widely available blood markers produces effective blood tests for cancer for NHS 2WW patients. The tests are affordable, and can be deployed rapidly to any NHS pathology laboratory with no additional hardware requirements.