A Small-area Data Analysis for Cancer Registration Data of Busan

BackgroundFor the majority of cancer patients, the length of the diagnostic pathway is unknown. Only those on a specific pathway are monitored. Quantifying pathway length is important in understating which patients may benefit most from an expedited pathway. AimThis study aimed to develop a novel methodology using linked cancer registration data to calculate the Secondary Care Diagnostic Interval (SDCI): the period from first interaction with secondary care to receiving a cancer diagnosis. Subsequently variation in SCDIs across twenty-five cancer sites were analysed. MethodsEnglish cancer registrations (2014-15) from Public Health England’s National Cancer Registration and Analysis Service were linked to three routine health datasets: Hospital Episode Statistics, Diagnostic Imaging Dataset and Cancer Waiting Times. The SCDI was calculated as the difference between the earliest event relating to the secondary care diagnostic process (comprised of referral into/secondary care appointment or diagnostic procedure in the 6 months before diagnosis) and the diagnosis date. SCDI length was stratified by stage at diagnosis, route to diagnosis (e.g. emergency presentation, GP referral) and patient characteristics. ResultsThe median SCDI (days) was shortest for acute lymphoblastic leukaemia (ALL) (2) and longest for kidney (45). In general, SCDIs decreased with later stage (for example stage 1-4 colorectal: 35 to 20, lung: 75 to 25). Patients diagnosed after routine GP referrals had longest SCDIs compared to urgent referrals, for all sites except ALL. Geographical variation in SCDIs exists by Cancer Alliance, with the greatest differences compared to the England average observed for prostate cancer (median national SCDI: 28, Cancer Alliance range: 21 - 42). ConclusionSubstantial variation exists in SCDIs by cancer site, stage and presentation route. Many patients are experiencing SCDIs over 28 days, even those diagnosed via urgent GP referrals. Understanding variation can support creation of targeted initiatives to expedite diagnostic pathways where appropriate.

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Cross-sectional study using primary care and cancer registration data to investigate patients with cancer presenting with non-specific symptoms

BMJ Open ◽

10.1136/bmjopen-2019-033008 ◽

2020 ◽

Vol 10 (1) ◽

pp. e033008 ◽

Cited By ~ 3

Author(s):

Clare Pearson ◽

Veronique Poirier ◽

Karen Fitzgerald ◽

Greg Rubin ◽

Willie Hamilton

Keyword(s):

Primary Care ◽

Cancer Diagnosis ◽

Cross Sectional Study ◽

Cancer Registration ◽

Sectional Study ◽

Cross Sectional ◽

Site Specific ◽

Registration Data ◽

Referral Criteria ◽

Specific Symptoms

IntroductionPatients presenting to primary care with site-specific alarm symptoms can be referred onto urgent suspected cancer pathways, whereas those with non-specific symptoms currently have no dedicated referral routes leading to delays in cancer diagnosis and poorer outcomes. Pilot Multidisciplinary Diagnostic Centres (MDCs) provide a referral route for such patients in England.ObjectivesThis work aimed to use linked primary care and cancer registration data to describe diagnostic pathways for patients similar to those being referred into MDCs and compare them to patients presenting with more specific symptoms.MethodsThis cross-sectional study linked primary care data from the National Cancer Diagnosis Audit (NCDA) to national cancer registration and Route to Diagnosis records. Patient symptoms recorded in the NCDA were used to allocate patients to one of two groups - those presenting with symptoms mirroring referral criteria of MDCs (non-specific but concerning symptoms (NSCS)) and those with at least one site-specific alarm symptom (non-NSCS). Descriptive analyses compared the two groups and regression analysis by group investigated associations with long primary care intervals (PCIs).ResultsPatients with NSCS were more likely to be diagnosed at later stage (32% stage 4, compared with 21% in non-NSCS) and via an emergency presentation (34% vs 16%). These patients also had more multiple pre-referral general practitioner consultations (59% vs 43%) and primary care-led diagnostics (blood tests: 57% vs 35%). Patients with NSCS had higher odds of having longer PCIs (adjusted OR: 1.24 (1.11 to 1.36)). Patients with lung and urological cancers also had higher odds of longer PCIs overall and in both groups.ConclusionsDifferences in the diagnostic pathway show that patients with symptoms mirroring the MDC referral criteria could benefit from a new referral pathway.

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What are the implications of using individual and combined sources of routinely collected data to identify and characterise incident site-specific cancers? a concordance and validation study using linked English electronic health records data

BMJ Open ◽

10.1136/bmjopen-2020-037719 ◽

2020 ◽

Vol 10 (8) ◽

pp. e037719

Author(s):

Helen Strongman ◽

Rachael Williams ◽

Krishnan Bhaskaran

Keyword(s):

Primary Care ◽

Gold Standard ◽

Cancer Registration ◽

Data Sets ◽

Death Registration ◽

Case Definitions ◽

Predictive Values ◽

Site Specific ◽

Registration Data ◽

Electronic Health

ObjectivesTo describe the benefits and limitations of using individual and combinations of linked English electronic health data to identify incident cancers.Design and settingOur descriptive study uses linked English Clinical Practice Research Datalink primary care; cancer registration; hospitalisation and death registration data.Participants and measuresWe implemented case definitions to identify first site-specific cancers at the 20 most common sites, based on the first ever cancer diagnosis recorded in each individual or commonly used combination of data sources between 2000 and 2014. We calculated positive predictive values and sensitivities of each definition, compared with a gold standard algorithm that used information from all linked data sets to identify first cancers. We described completeness of grade and stage information in the cancer registration data set.Results165 953 gold standard cancers were identified. Positive predictive values of all case definitions were ≥80% and ≥94% for the four most common cancers (breast, lung, colorectal and prostate). Sensitivity for case definitions that used cancer registration alone or in combination was ≥92% for the four most common cancers and ≥80% across all cancer sites except bladder cancer (65% using cancer registration alone). For case definitions using linked primary care, hospitalisation and death registration data, sensitivity was ≥89% for the four most common cancers, and ≥80% for all cancer sites except kidney (69%), oral cavity (76%) and ovarian cancer (78%). When primary care or hospitalisation data were used alone, sensitivities were generally lower and diagnosis dates were delayed. Completeness of staging data in cancer registration data was high from 2012 (minimum 76.0% in 2012 and 86.4% in 2014 for the four most common cancers).ConclusionsAscertainment of incident cancers was good when using cancer registration data alone or in combination with other data sets, and for the majority of cancers when using a combination of primary care, hospitalisation and death registration data.

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