| dc.description.abstract | Background: Tools based on diagnostic prediction models are available to help general practitioners
diagnose cancer. It is unclear whether or not tools expedite diagnosis or affect patient quality of life
and/or survival.
Objectives: The objectives were to evaluate the evidence on the validation, clinical effectiveness,
cost-effectiveness, and availability and use of cancer diagnostic tools in primary care.
Methods: Two systematic reviews were conducted to examine the clinical effectiveness (review 1) and
the development, validation and accuracy (review 2) of diagnostic prediction models for aiding general
practitioners in cancer diagnosis. Bibliographic searches were conducted on MEDLINE, MEDLINE
In-Process, EMBASE, Cochrane Library and Web of Science) in May 2017, with updated searches
conducted in November 2018. A decision-analytic model explored the tools’ clinical effectiveness and
cost-effectiveness in colorectal cancer. The model compared patient outcomes and costs between
strategies that included the use of the tools and those that did not, using the NHS perspective. We
surveyed 4600 general practitioners in randomly selected UK practices to determine the proportions
of general practices and general practitioners with access to, and using, cancer decision support tools.
Association between access to these tools and practice-level cancer diagnostic indicators was explored.
Results: Systematic review 1 – five studies, of different design and quality, reporting on three diagnostic
tools, were included. We found no evidence that using the tools was associated with better outcomes.
Systematic review 2 – 43 studies were included, reporting on prediction models, in various stages of
development, for 14 cancer sites (including multiple cancers). Most studies relate to QCancer® (ClinRisk
Ltd, Leeds, UK) and risk assessment tools.
Decision model: In the absence of studies reporting their clinical outcomes, QCancer and risk
assessment tools were evaluated against faecal immunochemical testing. A linked data approach
was used, which translates diagnostic accuracy into time to diagnosis and treatment, and stage at diagnosis. Given the current lack of evidence, the model showed that the cost-effectiveness of
diagnostic tools in colorectal cancer relies on demonstrating patient survival benefits. Sensitivity of
faecal immunochemical testing and specificity of QCancer and risk assessment tools in a low-risk
population were the key uncertain parameters.
Survey: Practitioner- and practice-level response rates were 10.3% (476/4600) and 23.3% (227/975),
respectively. Cancer decision support tools were available in 83 out of 227 practices (36.6%,
95% confidence interval 30.3% to 43.1%), and were likely to be used in 38 out of 227 practices
(16.7%, 95% confidence interval 12.1% to 22.2%). The mean 2-week-wait referral rate did not differ
between practices that do and practices that do not have access to QCancer or risk assessment tools
(mean difference of 1.8 referrals per 100,000 referrals, 95% confidence interval –6.7 to 10.3 referrals
per 100,000 referrals).
Limitations: There is little good-quality evidence on the clinical effectiveness and cost-effectiveness
of diagnostic tools. Many diagnostic prediction models are limited by a lack of external validation.
There are limited data on current UK practice and clinical outcomes of diagnostic strategies, and
there is no evidence on the quality-of-life outcomes of diagnostic results. The survey was limited
by low response rates.
Conclusion: The evidence base on the tools is limited. Research on how general practitioners interact
with the tools may help to identify barriers to implementation and uptake, and the potential for
clinical effectiveness.
Future work: Continued model validation is recommended, especially for risk assessment tools.
Assessment of the tools’ impact on time to diagnosis and treatment, stage at diagnosis, and health
outcomes is also recommended, as is further work to understand how tools are used in general
practitioner consultations.
Study registration: This study is registered as PROSPERO CRD42017068373 and CRD42017068375. | en_GB |
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