Publications by category
Journal articles
Price SJ, Spencer A, Medina-Lara A, Hamilton W (In Press). Availability of cancer decision-support tools: a cross-sectional survey of UK primary care.
British Journal of General Practice Full text.
Ankus E, Price S, Ukoumunne O, Hamilton W, Bailey S (In Press). Cancer incidence in patients with a high normal platelet count: a cohort study using primary care data.
Family Practice Full text.
Price SJ, Stapley SA, Shephard E, Barraclough K, Hamilton WT (In Press). Is omission of free text records a possible source of data loss and bias in Clinical Practice Research Datalink studies? a case-control study.
BMJ Open,
6(5).
Abstract:
Is omission of free text records a possible source of data loss and bias in Clinical Practice Research Datalink studies? a case-control study.
OBJECTIVES: to estimate data loss and bias in studies of Clinical Practice Research Datalink (CPRD) data that restrict analyses to Read codes, omitting anything recorded as text. DESIGN: Matched case-control study. SETTING: Patients contributing data to the CPRD. PARTICIPANTS: 4915 bladder and 3635 pancreatic, cancer cases diagnosed between 1 January 2000 and 31 December 2009, matched on age, sex and general practitioner practice to up to 5 controls (bladder: n=21â€
718; pancreas: n=16â€
459). The analysis period was the year before cancer diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: Frequency of haematuria, jaundice and abdominal pain, grouped by recording style: Read code or text-only (ie, hidden text). The association between recording style and case-control status (χ(2) test). For each feature, the odds ratio (OR; conditional logistic regression) and positive predictive value (PPV; Bayes' theorem) for cancer, before and after addition of hidden text records. RESULTS: of the 20 958 total records of the features, 7951 (38%) were recorded in hidden text. Hidden text recording was more strongly associated with controls than with cases for haematuria (140/336=42% vs 556/3147=18%) in bladder cancer (χ(2) test, p
Abstract.
Author URL.
Full text.
Nicholson BD, Shinkins B, Price S, Verbakel JY, Merriel S (2018). National cancer control plans. The Lancet Oncology, 19(12).
Mounce LTA, Price S, Valderas JM, Hamilton W (2017). Comorbid conditions delay diagnosis of colorectal cancer: a cohort study using electronic primary care records.
Br J Cancer,
116(12), 1536-1543.
Abstract:
Comorbid conditions delay diagnosis of colorectal cancer: a cohort study using electronic primary care records.
BACKGROUND: Pre-existing non-cancer conditions may complicate and delay colorectal cancer diagnosis. METHOD: Incident cases (aged ⩾40 years, 2007-2009) with colorectal cancer were identified in the Clinical Practice Research Datalink, UK. Diagnostic interval was defined as time from first symptomatic presentation of colorectal cancer to diagnosis. Comorbid conditions were classified as 'competing demands' (unrelated to colorectal cancer) or 'alternative explanations' (sharing symptoms with colorectal cancer). The association between diagnostic interval (log-transformed) and age, gender, consultation rate and number of comorbid conditions was investigated using linear regressions, reported using geometric means. RESULTS: Out of the 4512 patients included, 72.9% had ⩾1 competing demand and 31.3% had ⩾1 alternative explanation. In the regression model, the numbers of both types of comorbid conditions were independently associated with longer diagnostic interval: a single competing demand delayed diagnosis by 10 days, and four or more by 32 days; and a single alternative explanation by 9 days. For individual conditions, the longest delay was observed for inflammatory bowel disease (26 days; 95% CI 14-39). CONCLUSIONS: the burden and nature of comorbidity is associated with delayed diagnosis in colorectal cancer, particularly in patients aged ⩾80 years. Effective clinical strategies are needed for shortening diagnostic interval in patients with comorbidity.
Abstract.
Author URL.
Full text.
Watson J, Nicholson BD, Hamilton W, Price S (2017). Identifying clinical features in primary care electronic health record studies: methods for codelist development.
BMJ Open,
7(11).
Abstract:
Identifying clinical features in primary care electronic health record studies: methods for codelist development.
OBJECTIVE: Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. DESIGN: We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis. SETTING: These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. PARTICIPANTS: the codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). RESULTS: of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. CONCLUSIONS: Although initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review.
Abstract.
Author URL.
Full text.
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2015). Does the GP method of recording possible cancer symptoms reflect the probability that cancer is present?.
EUROPEAN JOURNAL OF CANCER CARE,
24, 30-30.
Author URL.
Full text.
Martins T, Price S, Hjertholm P, Hamilton W (2015). Doing PhD in primary care diagnosis and treatment of cancer.
EUROPEAN JOURNAL OF CANCER CARE,
24, 58-58.
Author URL.
Full text.
Brown JM, Price SJ, Price RA (2015). Predicting risk after aneurysm surgery.
Anaesthesia,
70(11).
Author URL.
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2014). Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care. British Journal of General Practice, 626(64), 584-589.
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2014). Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care.
Br J Gen Pract,
64(626), e584-e589.
Abstract:
Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care.
BACKGROUND: Diagnosis of bladder cancer relies on investigation of symptoms presented to primary care, notably visible haematuria. The importance of non-visible haematuria has never been estimated. AIM: to estimate the risk of bladder cancer with non-visible haematuria. DESIGN AND SETTING: a case-control study using UK electronic primary care medical records, including uncoded data to supplement coded records. METHOD: a total of 4915 patients (aged ≥40 years) diagnosed with bladder cancer between January 2000 and December 2009 were selected from the Clinical Practice Research Datalink and matched to 21 718 controls for age, sex, and practice. Variables for visible and non-visible haematuria were derived from coded and uncoded data. Analyses used multivariable conditional logistic regression, followed by estimation of positive predictive values (PPVs) for bladder cancer using Bayes' theorem. RESULTS: Non-visible haematuria (coded/uncoded data) was independently associated with bladder cancer: odds ratio (OR) 20 (95% confidence interval [CI] =12 to 33). The PPV of non-visible haematuria was 1.6% (95% CI = 1.2 to 2.1) in those aged ≥60 years and 0.8% (95% CI = 0.1 to 5.6) in 40-59-year-olds. The PPV of visible haematuria was 2.8% (95% CI = 2.5 to 3.1) and 1.2% (95% CI = 0.6 to 2.3) for the same age groups respectively, lower than those calculated using coded data alone. The proportion of records of visible haematuria in coded, rather than uncoded, format was higher in cases than in controls (P
Abstract.
Author URL.
Full text.
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2014). The risk of bladder cancer with non-visible haematuria: a primary care study using electronic records.
EUROPEAN JOURNAL OF CANCER CARE,
23, 32-32.
Author URL.
Full text.
Poole RC, Halestrap AP, Price SJ, Levi AJ (1989). The kinetics of transport of lactate and pyruvate into isolated cardiac myocytes from guinea pig. Kinetic evidence for the presence of a carrier distinct from that in erythrocytes and hepatocytes. Biochemical Journal, 264(2), 409-418.
Chapters
Price SJ, Price R, Hamilton W (2018). Clinical and other diagnostic tests: understanding their predictive value. In (Ed)
How to Do Primary Care Research, Boca Raton: CRC Press.
Abstract:
Clinical and other diagnostic tests: understanding their predictive value
Abstract.
Conferences
Bailey SER, Ankus E, Price S, Pula G, Hamilton W (2018). The diagnostic potential of 'high normal' platelet counts for identifying cancer in primary care.
Author URL.
Publications by year
In Press
Price SJ, Spencer A, Medina-Lara A, Hamilton W (In Press). Availability of cancer decision-support tools: a cross-sectional survey of UK primary care.
British Journal of General Practice Full text.
Ankus E, Price S, Ukoumunne O, Hamilton W, Bailey S (In Press). Cancer incidence in patients with a high normal platelet count: a cohort study using primary care data.
Family Practice Full text.
Price SJ, Stapley SA, Shephard E, Barraclough K, Hamilton WT (In Press). Is omission of free text records a possible source of data loss and bias in Clinical Practice Research Datalink studies? a case-control study.
BMJ Open,
6(5).
Abstract:
Is omission of free text records a possible source of data loss and bias in Clinical Practice Research Datalink studies? a case-control study.
OBJECTIVES: to estimate data loss and bias in studies of Clinical Practice Research Datalink (CPRD) data that restrict analyses to Read codes, omitting anything recorded as text. DESIGN: Matched case-control study. SETTING: Patients contributing data to the CPRD. PARTICIPANTS: 4915 bladder and 3635 pancreatic, cancer cases diagnosed between 1 January 2000 and 31 December 2009, matched on age, sex and general practitioner practice to up to 5 controls (bladder: n=21â€
718; pancreas: n=16â€
459). The analysis period was the year before cancer diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: Frequency of haematuria, jaundice and abdominal pain, grouped by recording style: Read code or text-only (ie, hidden text). The association between recording style and case-control status (χ(2) test). For each feature, the odds ratio (OR; conditional logistic regression) and positive predictive value (PPV; Bayes' theorem) for cancer, before and after addition of hidden text records. RESULTS: of the 20 958 total records of the features, 7951 (38%) were recorded in hidden text. Hidden text recording was more strongly associated with controls than with cases for haematuria (140/336=42% vs 556/3147=18%) in bladder cancer (χ(2) test, p
Abstract.
Author URL.
Full text.
2018
Price SJ, Price R, Hamilton W (2018). Clinical and other diagnostic tests: understanding their predictive value. In (Ed)
How to Do Primary Care Research, Boca Raton: CRC Press.
Abstract:
Clinical and other diagnostic tests: understanding their predictive value
Abstract.
Nicholson BD, Shinkins B, Price S, Verbakel JY, Merriel S (2018). National cancer control plans. The Lancet Oncology, 19(12).
Bailey SER, Ankus E, Price S, Pula G, Hamilton W (2018). The diagnostic potential of 'high normal' platelet counts for identifying cancer in primary care.
Author URL.
2017
Mounce LTA, Price S, Valderas JM, Hamilton W (2017). Comorbid conditions delay diagnosis of colorectal cancer: a cohort study using electronic primary care records.
Br J Cancer,
116(12), 1536-1543.
Abstract:
Comorbid conditions delay diagnosis of colorectal cancer: a cohort study using electronic primary care records.
BACKGROUND: Pre-existing non-cancer conditions may complicate and delay colorectal cancer diagnosis. METHOD: Incident cases (aged ⩾40 years, 2007-2009) with colorectal cancer were identified in the Clinical Practice Research Datalink, UK. Diagnostic interval was defined as time from first symptomatic presentation of colorectal cancer to diagnosis. Comorbid conditions were classified as 'competing demands' (unrelated to colorectal cancer) or 'alternative explanations' (sharing symptoms with colorectal cancer). The association between diagnostic interval (log-transformed) and age, gender, consultation rate and number of comorbid conditions was investigated using linear regressions, reported using geometric means. RESULTS: Out of the 4512 patients included, 72.9% had ⩾1 competing demand and 31.3% had ⩾1 alternative explanation. In the regression model, the numbers of both types of comorbid conditions were independently associated with longer diagnostic interval: a single competing demand delayed diagnosis by 10 days, and four or more by 32 days; and a single alternative explanation by 9 days. For individual conditions, the longest delay was observed for inflammatory bowel disease (26 days; 95% CI 14-39). CONCLUSIONS: the burden and nature of comorbidity is associated with delayed diagnosis in colorectal cancer, particularly in patients aged ⩾80 years. Effective clinical strategies are needed for shortening diagnostic interval in patients with comorbidity.
Abstract.
Author URL.
Full text.
Watson J, Nicholson BD, Hamilton W, Price S (2017). Identifying clinical features in primary care electronic health record studies: methods for codelist development.
BMJ Open,
7(11).
Abstract:
Identifying clinical features in primary care electronic health record studies: methods for codelist development.
OBJECTIVE: Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. DESIGN: We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis. SETTING: These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. PARTICIPANTS: the codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). RESULTS: of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. CONCLUSIONS: Although initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review.
Abstract.
Author URL.
Full text.
2015
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2015). Does the GP method of recording possible cancer symptoms reflect the probability that cancer is present?.
EUROPEAN JOURNAL OF CANCER CARE,
24, 30-30.
Author URL.
Full text.
Martins T, Price S, Hjertholm P, Hamilton W (2015). Doing PhD in primary care diagnosis and treatment of cancer.
EUROPEAN JOURNAL OF CANCER CARE,
24, 58-58.
Author URL.
Full text.
Brown JM, Price SJ, Price RA (2015). Predicting risk after aneurysm surgery.
Anaesthesia,
70(11).
Author URL.
2014
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2014). Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care. British Journal of General Practice, 626(64), 584-589.
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2014). Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care.
Br J Gen Pract,
64(626), e584-e589.
Abstract:
Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care.
BACKGROUND: Diagnosis of bladder cancer relies on investigation of symptoms presented to primary care, notably visible haematuria. The importance of non-visible haematuria has never been estimated. AIM: to estimate the risk of bladder cancer with non-visible haematuria. DESIGN AND SETTING: a case-control study using UK electronic primary care medical records, including uncoded data to supplement coded records. METHOD: a total of 4915 patients (aged ≥40 years) diagnosed with bladder cancer between January 2000 and December 2009 were selected from the Clinical Practice Research Datalink and matched to 21 718 controls for age, sex, and practice. Variables for visible and non-visible haematuria were derived from coded and uncoded data. Analyses used multivariable conditional logistic regression, followed by estimation of positive predictive values (PPVs) for bladder cancer using Bayes' theorem. RESULTS: Non-visible haematuria (coded/uncoded data) was independently associated with bladder cancer: odds ratio (OR) 20 (95% confidence interval [CI] =12 to 33). The PPV of non-visible haematuria was 1.6% (95% CI = 1.2 to 2.1) in those aged ≥60 years and 0.8% (95% CI = 0.1 to 5.6) in 40-59-year-olds. The PPV of visible haematuria was 2.8% (95% CI = 2.5 to 3.1) and 1.2% (95% CI = 0.6 to 2.3) for the same age groups respectively, lower than those calculated using coded data alone. The proportion of records of visible haematuria in coded, rather than uncoded, format was higher in cases than in controls (P
Abstract.
Author URL.
Full text.
Price SJ, Shephard EA, Stapley SA, Barraclough K, Hamilton WT (2014). The risk of bladder cancer with non-visible haematuria: a primary care study using electronic records.
EUROPEAN JOURNAL OF CANCER CARE,
23, 32-32.
Author URL.
Full text.
1989
Poole RC, Halestrap AP, Price SJ, Levi AJ (1989). The kinetics of transport of lactate and pyruvate into isolated cardiac myocytes from guinea pig. Kinetic evidence for the presence of a carrier distinct from that in erythrocytes and hepatocytes. Biochemical Journal, 264(2), 409-418.
