Symptoms and risk factors to identify women with suspected cancer in primary care: derivation and validation of an algorithm

Hippisley‐Cox, Julia; Coupland, Carol

doi:10.3399/bjgp13x660733

Cited by 110 publications

(145 citation statements)

References 27 publications

(54 reference statements)

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“…127,128 This approach allows the independent eff ects of several clinically important factors to be estimated: high-risk symptoms such as weight loss, abdominal pain, indigestion, dysphagia, abnormal bleeding, and lumps; general non-specifi c symptoms such as tiredness and constipation; and risk factors such as age, family history, smoking status, alcohol intake, deprivation, body-mass index (BMI), and current medical conditions. Regression analysis enables the development of a risk equation for an overall risk of cancer based on the combined elements of diff erent cancers.…”

Section: Epidemiology Of Cancer Symptomsmentioning

confidence: 99%

The expanding role of primary care in cancer control

Rubin

Berendsen

Crawford

et al. 2015

The Lancet Oncology

437

450

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The nature of cancer control is changing, with an increasing emphasis, fuelled by public and political demand, on prevention, early diagnosis, and patient experience during and after treatment. At the same time, primary care is increasingly promoted, by governments and health funders worldwide, as the preferred setting for most health care for reasons of increasing need, to stabilise health-care costs, and to accommodate patient preference for care close to home. It is timely, then, to consider how this expanding role for primary care can work for cancer control, which has long been dominated by highly technical interventions centred on treatment, and in which the contribution of primary care has been largely perceived as marginal. In this Commission, expert opinion from primary care and public health professionals with academic and clinical cancer expertise-from epidemiologists, psychologists, policy makers, and cancer specialists-has contributed to a detailed consideration of the evidence for cancer control provided in primary care and community care settings. Ranging from primary prevention to end-of-life care, the scope for new models of care is explored, and the actions needed to eff ect change are outlined. The strengths of primary care-its continuous, coordinated, and comprehensive care for individuals and families-are particularly evident in prevention and diagnosis, in shared follow-up and survivorship care, and in end-of-life care. A strong theme of integration of care runs throughout, and its elements (clinical, vertical, and functional) and the tools needed for integrated working are described in detail. All of this change, as it evolves, will need to be underpinned by new research and by continuing and shared multiprofessional development.

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Section: Epidemiology Of Cancer Symptomsmentioning

confidence: 99%

The expanding role of primary care in cancer control

Rubin

Berendsen

Crawford

et al. 2015

The Lancet Oncology

437

450

View full text Add to dashboard Cite

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“…It is important that health professionals identify and communicate possible risks associated with cancer to swiftly refer any patient with suspected disease to ensure continuity of care. 68 In Mexico, López-Carrillo showed that 90% of women surveyed in three hospitals nationwide had identified the presence of a lump in their breast on their own. 30 The time to being re-called for biopsy is an essential component of a program's success.…”

Section: Signs and Symptomsmentioning

confidence: 99%

Effect of care-delivery delay on the survival of Mexican women with breast cancer

et al. 2016

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Efecto de la demora en la atención sobre la supervivencia de mujeres mexicanas con cáncer de mama. Salud Publica Mex 2016;58:237-250. ResumenObjetivo. Estimar el efecto del tiempo de atención sobre la supervivencia de mujeres con cáncer de mama. Material y métodos. Se realizó el análisis retrospectivo de 854 mujeres atendidas en 11 hospitales entre 2007 y 2009. Se emplearon estimadores de Kaplan-Meier y un modelo de riesgos proporcionales de Cox. Resultados. 10.5% se diagnosticó en etapa I, mientras que 82.1% demoró más de 67 días entre la percepción de un síntoma y el inicio del tratamiento. La mediana del tiempo desde la entrega de los resultados de la mastografía hasta la biopsia fue de 31 días (RIQ 14-56); en comparación con quienes se encontraron en el cuartil 1 (Q1), la supervivencia fue menor en aquellas que se encontraron en los Q3 y Q4 (HR=1.68, IC95% 0.94-3.00; HR=1.76, IC95% 1.04-2.98, respectivamente). Conclusiones. Se sugiere reducir el tiempo desde la entrega de los resultados de la mastografía a la biopsia diagnóstica para incrementar la supervivencia.Palabras clave: cáncer de mama; demora en la atención; supervivencia; México The median time from receipt of results of the mammography to biopsy was 31 days (IQR 14-56). Compared with those who were in quartile I (Q1), survival was lower among those in Q3 and Q4 (HR=1.68, 95%CI 0.94-3.00; HR=1.76, 95% CI 1.04-2.98, respectively). Conclusions. To increase survival, it is suggested that the time between receipt of the mammography results and diagnostic biopsy be reduced.

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“…Other countries with an electronic referral system may use the explained stepped approach to develop a comparable algorithm. The essential studies on PPVs for symptoms of cancer and the QCancer web tool are based on word recognition from routinely collected patient data in a large number of GP clinics in England 21–29. However, to our knowledge, no other studies have reported the methodological development of an algorithm aiming to sample specific patient populations through pattern recognition of word strings and text fields in referral letters.…”

Section: Discussionmentioning

confidence: 99%

Development of an algorithm to identify urgent referrals for suspected cancer from the Danish Primary Care Referral Database

Toftegaard¹,

Guldbrandt²,

Flarup

et al. 2016

CLEP

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BackgroundAccurate identification of specific patient populations is a crucial tool in health care. A prerequisite for exploring the actions taken by general practitioners (GPs) on symptoms of cancer is being able to identify patients urgently referred for suspected cancer. Such system is not available in Denmark; however, all referrals are electronically stored. This study aimed to develop and test an algorithm based on referral text to identify urgent cancer referrals from general practice.MethodsTwo urgently referred reference populations were extracted from a research database and linked with the Primary Care Referral (PCR) database through the unique Danish civil registration number to identify the corresponding electronic referrals. The PCR database included GP referrals directed to private specialists and hospital departments, and these referrals were scrutinized. The most frequently used words were integrated in the first version of the algorithm, which was further refined by an iterative process involving two population samples from the PCR database. The performance was finally evaluated for two other PCR population samples against manual assessment as the gold standard for urgent cancer referral.ResultsThe final algorithm had a sensitivity of 0.939 (95% confidence intervals [CI]: 0.905–0.963) and a specificity of 0.937 (95% CI: 0.925–0.963) compared to the gold standard. The positive and negative predictive values were 69.8% (95% CI: 65.0–74.3) and 99.0% (95% CI: 98.4–99.4), respectively. When applying the algorithm on referrals for a population without earlier cancer diagnoses, the positive predictive value increased to 83.6% (95% CI: 78.7–87.7) and the specificity to 97.3% (95% CI: 96.4–98.0).ConclusionThe final algorithm identified 94% of the patients urgently referred for suspected cancer; less than 3% of the patients were incorrectly identified. It is now possible to identify patients urgently referred on cancer suspicion from general practice by applying an algorithm for populations in the PCR database.

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Symptoms and risk factors to identify women with suspected cancer in primary care: derivation and validation of an algorithm

Cited by 110 publications

References 27 publications

The expanding role of primary care in cancer control

The expanding role of primary care in cancer control

Effect of care-delivery delay on the survival of Mexican women with breast cancer

Development of an algorithm to identify urgent referrals for suspected cancer from the Danish Primary Care Referral Database

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