Availability and use of cancer decision-support tools: a cross-sectional survey of UK primary care

Price, Sarah; Spencer, Anne; Medina-Lara, Antonieta; Hamilton, William

doi:10.3399/bjgp19x703745

Cited by 38 publications

(48 citation statements)

References 38 publications

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“…Multivariable approaches to cancer risk prediction may better capture the complex associations that are present in clinical practice, 59 but uptake into routine primary care practice is poor 60 and models are built using coded electronic health records data, 61 thereby excluding free-text data that is more likely to contain information recorded about non-verbal cues. 62 Non-verbal cues, such as deviations from patients' usual presentation pattern or appearance, represent aspects of clinical practice that are more difficult to standardise and codify, making their integration into evidence-based guidelines problematic.…”

Section: Comparison With Existing Literaturementioning

confidence: 99%

Understanding the role of GPs’ gut feelings in diagnosing cancer in primary care: a systematic review and meta-analysis of existing evidence

et al. 2020

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BackgroundGrowing evidence for the role of GPs’ gut feelings in cancer diagnosis raises questions about their origin and role in clinical practice.AimTo explore the origins of GPs’ gut feelings for cancer, their use, and their diagnostic utility.Design and settingSystematic review and meta-analysis of international research on GPs’ gut feelings in primary care.MethodSix databases were searched from inception to July 2019, and internet searches were conducted. A segregated method was used to analyse, then combine, quantitative and qualitative findings.ResultsTwelve articles and four online resources were included that described varied conceptualisations of gut feelings. Gut feelings were often initially associated with patients being unwell, rather than with a suspicion of cancer, and were commonly experienced in response to symptoms and non-verbal cues. The pooled odds of a cancer diagnosis were four times higher when gut feelings were recorded (OR 4.24, 95% confidence interval = 2.26 to 7.94); they became more predictive of cancer as clinical experience and familiarity with the patient increased. Despite being included in some clinical guidelines, GPs had varying experiences of acting on gut feelings as some specialists questioned their diagnostic value. Consequently, some GPs ignored or omitted gut feelings from referral letters, or chose investigations that did not require specialist approval.ConclusionGPs’ gut feelings for cancer were conceptualised as a rapid summing up of multiple verbal and non-verbal patient cues in the context of the GPs’ clinical knowledge and experience. Triggers of gut feelings not included in referral guidance deserve further investigation as predictors of cancer. Non-verbal cues that trigger gut feelings appear to be reliant on continuity of care and clinical experience; they tend to remain poorly recorded and are, therefore, inaccessible to researchers.

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Section: Comparison With Existing Literaturementioning

confidence: 99%

Understanding the role of GPs’ gut feelings in diagnosing cancer in primary care: a systematic review and meta-analysis of existing evidence

et al. 2020

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“…In fact, recent research in this area indicates cancer decision support tools which include QCancer are not being widely used. 14 The aim of this study was to explore the views of service users and primary care practitioners on how best to communicate cancer risk information when using QCancer, a cancer risk assessment tool, with symptomatic individuals in primary care consultations to enable them be involved in decisions on referral and cancer investigations.…”

Section: Backg Rou N Dmentioning

confidence: 99%

“…While there is existing literature about communicating and sharing decisions with people who have cancer, most communication evidence relates to people with existing cancer, but is not directly related to the use of cancer risk assessment tools designed for individuals with symptoms reporting to primary care who may not yet be aware of their cancer status. In fact, recent research in this area indicates cancer decision support tools which include QCancer are not being widely used …”

Section: Introductionmentioning

confidence: 99%

Communicating cancer risk in the primary care consultation when using a cancer risk assessment tool: Qualitative study with service users and practitioners

Akanuwe

Black

Owen

et al. 2020

Health Expectations

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Background Cancer risk assessment tools are designed to help detect cancer risk in symptomatic individuals presenting to primary care. An early detection of cancer risk could mean early referral for investigations, diagnosis and treatment, helping to address late diagnosis of cancer. It is not clear how best cancer risk may be communicated to patients when using a cancer risk assessment tool to assess their risk of developing cancer. Objective We aimed to explore the perspectives of service users and primary care practitioners on communicating cancer risk information to patients, when using QCancer, a cancer risk assessment tool. Design A qualitative study involving the use of individual interviews and focus groups. Setting and participants Conducted in primary care settings in Lincolnshire with a convenience sample of 36 participants (19 service users who were members of the public) and 17 primary care practitioners (general practitioners and practice nurses). Results Participants suggested ways to improve communication of cancer risk information: personalizing risk information; involving patients in use of the tool; sharing risk information openly; and providing sufficient time when using the tool during consultations. Conclusion Communication of cancer risk information is complex and difficult. We identified strategies for improving communication with patients involving cancer risk estimations in primary care consultations.

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“…A similar model has been used successfully in the Netherlands for referrals of patients with possible prostate cancer, having a positive predictive value of 79% and a 100% negative predictive value for clinically significant prostate cancer (Gleason >7) 24. On the other hand, a recent survey of UK general practices showed that only 36% have access to cancer decision support tools, and only 16% are likely to use them 25. Possible reasons for the underuse of such resources include the fact that some normograms require investigations that are not available to the primary care sector, and that in some cases, several calculators are available, with little guidance on which one to use.…”

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confidence: 99%

Head and neck cancer risk calculator (HaNC‐RC)—V.2. Adjustments and addition of symptoms and social history factors

Tikka

Kavanagh

Lowit

et al. 2020

Clinical Otolaryngology

105

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Objectives: Head and neck cancer (HNC) diagnosis through the 2-week wait, urgent suspicion of cancer (USOC) pathway has failed to increase early cancer detection rates in the UK. A head and neck cancer risk calculator (HaNC-RC) has previously been designed to aid referral of high-risk patients to USOC clinics (predictive power: 77%). Our aim was to refine the HaNC-RC to increase its prediction potential. Design: Following sample size calculation, prospective data collection and statistical analysis of referral criteria and outcomes. Setting: Large tertiary care cancer centre in Scotland. Participants: 3531 new patients seen in routine, urgent and USOC head and neck (HaN) clinics. Main outcome measures: Data collected were as follows: demographics, social history, presenting symptoms and signs and HNC diagnosis. Univariate and multivariate regression analysis were performed to identify significant predictors of HNC. Internal validation was performed using 1000 sample bootstrapping to estimate model diagnostics included the area under the receiver operator curve (AUC), sensitivity and specificity. Results:The updated version of the risk calculator (HaNC-RC v.2) includes age, gender, unintentional weight loss, smoking, alcohol, positive and negative symptoms and signs of HNC. It has achieved an AUC of 88.6% with two recommended triage referral cut-offs to USOC (cut-off: 7.1%; sensitivity: 85%, specificity: 78.3%) or urgent clinics (cut-off: 2.2%; sensitivity: 97.1%; specificity of 52.9%). This could redistribute cancer detection through USOC clinics from the current 60.9%-85.2%, without affecting total numbers seen in each clinical setting. Conclusions:The use of the HaNC-RC v.2 has a significant potential in both identifying patients at high risk of HNC early thought USOC clinics but also improving health service delivery practices by reducing the number of inappropriately urgent referrals. | 381TIKKA eT Al.

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Availability and use of cancer decision-support tools: a cross-sectional survey of UK primary care

Cited by 38 publications

References 38 publications

Understanding the role of GPs’ gut feelings in diagnosing cancer in primary care: a systematic review and meta-analysis of existing evidence

Understanding the role of GPs’ gut feelings in diagnosing cancer in primary care: a systematic review and meta-analysis of existing evidence

Communicating cancer risk in the primary care consultation when using a cancer risk assessment tool: Qualitative study with service users and practitioners

Head and neck cancer risk calculator (HaNC‐RC)—V.2. Adjustments and addition of symptoms and social history factors

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