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1. IL7 genetic variation and toxicity to immune checkpoint blockade in patients with melanoma

Author

Taylor, Chelsea A., Watson, Robert A., Tong, Orion, Ye, Weiyu, Nassiri, Isar, Gilchrist, James J., de los Aires, Alba Verge, Sharma, Piyush Kumar, Koturan, Surya, Cooper, Rosalin A., Woodcock, Victoria K., Jungkurth, Elsita, Shine, Brian, Coupe, Nicholas, Payne, Miranda J., Church, David N., Naranbhai, Vivek, Groha, Stefan, Emery, Paul, Mankia, Kulveer, Freedman, Matthew L., Choueiri, Toni K., Middleton, Mark R., Gusev, Alexander, and Fairfax, Benjamin P.

Published
2022
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6. Evaluation of a Simple Low-cost Intervention to Empower People with CKD to Reduce Their Dietary Salt Intake: OxCKD1, a Multicenter Randomized Controlled Trial

Author

O'Callaghan, Christopher A., primary, Camidge, Clare, additional, Thomas, Rachel, additional, Reschen, Michael E., additional, Maycock, Alison J., additional, Lasserson, Daniel S., additional, Fox, Robin A., additional, Thomas, Nicholas P.B., additional, Shine, Brian, additional, and James, Tim, additional

Published
2023
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9. Reduction in Chest CT Severity and Improved Hospital Outcomes in SARS-CoV-2 Omicron Compared with Delta Variant Infection

Author

Tsakok, Maria T., primary, Watson, Robert A., additional, Saujani, Shyamal J., additional, Kong, Mark, additional, Xie, Cheng, additional, Peschl, Heiko, additional, Wing, Louise, additional, MacLeod, Fiona K., additional, Shine, Brian, additional, Talbot, Nicholas P., additional, Benamore, Rachel E., additional, Eyre, David W., additional, and Gleeson, Fergus, additional

Published
2023
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12. Additional file 1 of Combining faecal immunochemical testing with blood test results for colorectal cancer risk stratification: a consecutive cohort of 16,604 patients presenting to primary care

Author

Withrow, Diana R., Shine, Brian, Oke, Jason, Tamm, Andres, James, Tim, Morris, Eva, Davies, Jim, Harris, Steve, East, James E., and Nicholson, Brian D.

Abstract

Additional file 1: Table S1. [Frequency of abnormal blood test results by outcome and FIT score]. Table S2. [Distribution of test results within study population by approach]. Table S3. [Model parameters for models resulting from backward stepwise regression]. Table S4. [Characteristics of patients receiving symptomatic FIT tests by date of FIT relative to COVID-19 pandemic]. Table S5. [Test performance comparing pre and post COVID19]. Table S6. [Test performance by demographic and clinical subgroups]. Table S7. [Test performance by subgroups defined by increasingly severe anaemia]. Table S8. [Test performance comparing patients who meet the DG30 criteria]. Table S9. [Test performance with 12 months of follow-up, FIT alone and FIT-blood test pairs]. Table S10. [Test performance with 12 months of follow-up, FIT alone and model-based approach.]. Table S11. [Predictive performance of abnormal blood tests among patients who are FIT negative].

Published
2022
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14. Long-term monitoring in primary care for chronic kidney disease and chronic heart failure: a multi-method research programme

Author

Perera, Rafael, primary, Stevens, Richard, additional, Aronson, Jeffrey K, additional, Banerjee, Amitava, additional, Evans, Julie, additional, Feakins, Benjamin G, additional, Fleming, Susannah, additional, Glasziou, Paul, additional, Heneghan, Carl, additional, Hobbs, FD Richard, additional, Jones, Louise, additional, Kurtinecz, Milena, additional, Lasserson, Daniel S, additional, Locock, Louise, additional, McLellan, Julie, additional, Mihaylova, Borislava, additional, O’Callaghan, Christopher A, additional, Oke, Jason L, additional, Pidduck, Nicola, additional, Plüddemann, Annette, additional, Roberts, Nia, additional, Schlackow, Iryna, additional, Shine, Brian, additional, Simons, Claire L, additional, Taylor, Clare J, additional, Taylor, Kathryn S, additional, Verbakel, Jan Y, additional, and Bankhead, Clare, additional

Published
2021
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15. Additional file 1 of Broad external validation of a multivariable risk prediction model for gastrointestinal malignancy in iron deficiency anaemia

Author

Almilaji, Orouba, Webb, Gwilym, Maynard, Alec, Chapman, Thomas P., Shine, Brian S. F., Ellis, Antony J., Hebden, John, Docherty, Sharon, Williams, Elizabeth J., and Snook, Jonathon

Abstract

Additional file 1: Table S1. Model coefficients before/after applying different regularisation methods. Figure S1. Average 95% confidence interval width for the C-statistic (discrimination) at different effective sample sizes comparing by SD(LP) at fixed base probability = 0.084. Figure S2. Average 95% confidence interval width for the calibration slope at different effective sample sizes (based on number of events) comparing by SD(LP) at fixed base probability =0.084. Table S2. Normal ranges for Hb, MCV, ferritin, T.sat in each lab. Figure S3. Density plots show the distributions of continuous variables per GI presence/absence in each dataset using IDIOM model. Figure S4. Density plots show the distribution of estimated risks per GI presence/absence in each dataset using IDIOM model. Figure S5. Risk groups calibration in the combined validation dataset shows the relation between the estimated risks (on the x-axis) and the observed risks (on the y-axis). Figure S6. Flexible calibration curve in Oxford dataset shows the relation between the estimated risks (on the x-axis) and the observed proportion of events (on the y-axis). Figure S7. Flexible calibration curve in Sheffield dataset shows the relation between the estimated risks (on the x-axis) and the observed proportion of events (on the y-axis). Figure S8. Decision curve analysis for GI investigation using Oxford dataset. Grey line: penalised IDIOM model. Black line: ���investigate no-one��� strategy. Dashed line: ���investigate all��� strategy. The vertical axis displays standardized net benefit. The horizontal axis shows the risk thresholds. Figure S9. Decision curve analysis for GI investigation using Sheffield dataset. Grey line: penalised IDIOM model. Black line: ���investigate no-one��� strategy. Dashed line: ���investigate all��� strategy. The vertical axis displays standardized net benefit. The horizontal axis shows the risk thresholds. Figure S10. Clinical impact curve for penalised IDIOM risk model using Dorset data, with 95% CIs constructed via bootstrapping. Of 1,000 patients, the heavy black solid line shows the total number who would be deemed low risk for each risk threshold. The blue dashed line shows how many of those would be true negatives. The vertical axis displays standardised net benefit. The two horizontal axes show the correspondence between risk threshold and cost:benefit ratio. Figure S11. Clinical impact curve for penalised IDIOM risk model using combined validation data from Oxford and Sheffield, with 95% CIs constructed via bootstrapping. Of 1,000 patients, the heavy black solid line shows the total number who would be deemed low risk for each risk threshold. The blue dashed line shows how many of those would be true negatives. The vertical axis displays standardised net benefit. The two horizontal axes show the correspondence between risk threshold and cost:benefit ratio. Figure S12. Clinical impact curve for penalised IDIOM risk model using the Oxford dataset, with 95% CIs constructed via bootstrapping. Of 1,000 patients, the heavy black solid line shows the total number who would be deemed low risk for each risk threshold. The blue dashed line shows how many of those would be true negatives. The vertical axis displays standardised net benefit. The two horizontal axes show the correspondence between risk threshold and cost:benefit ratio. Figure S13. Clinical impact curve for penalised IDIOM risk model using the Sheffield dataset, with 95% CIs constructed via bootstrapping. Of 1,000 patients, the heavy black solid line shows the total number who would be deemed low risk for each risk threshold. The blue dashed line shows how many of those would be true negatives. The vertical axis displays standardised net benefit. The two horizontal axes show the correspondence between risk threshold and cost:benefit ratio.

Published
2021
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16. Mutational Analysis of the Adaptor Protein 2 Sigma Subunit (AP2S1) Gene: Search for Autosomal Dominant Hypocalcemia Type 3 (ADH3)

Author

Rogers, Angela, Nesbit, M. Andrew, Hannan, Fadil M., Howles, Sarah A., Gorvin, Caroline M., Cranston, Treena, Allgrove, Jeremy, Bevan, John S., Bano, Gul, Brain, Caroline, Datta, Vipan, Grossman, Ashley B., Hodgson, Shirley V., Izatt, Louise, Millar-Jones, Lynne, Pearce, Simon H., Robertson, Lisa, Selby, Peter L., Shine, Brian, Snape, Katie, Warner, Justin, and Thakker, Rajesh V.

Published
2014

17. Frequency of Renal Monitoring — Creatinine and Cystatin C (FORM-2C): an observational cohort study of patients with reduced eGFR in primary care

Author

Fleming, Susannah, primary, Perera-Salazar, Rafael, additional, Taylor, Kathryn S, additional, Jones, Louise, additional, Hobbs, FD Richard, additional, James, Tim, additional, O’Callaghan, Chris A, additional, Shine, Brian, additional, Verbakel, Jan Y, additional, Stevens, Richard, additional, and Bankhead, Clare, additional

Published
2021
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19. An Adrenocortical Carcinoma Associated with Non-Islet Cell Tumor Hypoglycemia and Aberrant ACTH Production

Author

Dilrukshi, M. D. S. A., Wickramarachchi, A. W., Abeyaratne, D. D. K., Shine, Brian, Jafar-Mohammadi, Bahram, and Somasundaram, N. P.

Subjects
endocrine system, Article Subject
Abstract

Introduction. Adrenocortical carcinomas (ACCs) are infrequently reported to present with severe hypoglycemia syndrome resulting from the secretion of insulin-like growth factor II (IGF-II) by tumor cells. Adrenocorticotropic hormone- (ACTH) independent hypercortisolism is the norm of hormonally active ACCs, but aberrant ACTH production by tumor cells can theoretically cause ACTH-dependent hypercortisolism. The purpose of this report was to present a case of an ACC manifested with the co-occurrence of two extremely rare presentations. Case Description. We present a rare case of a 43-year-old male patient admitted with recurrent episodes of severe non-ketotic and non-insulin-mediated hypoglycemia due to IGF-II mediated disease and ACTH-dependent Cushing’s syndrome. He was diagnosed with a diffusely disseminated adrenocortical carcinoma with immunohistochemistry of tumor cells showing focal ACTH immunostain positivity. Conclusion. Non-islet cell tumor hypoglycemia and ACTH-dependent Cushing’s syndrome are extremely rare presentations of an ACC, and co-occurrence of these entities in a single patient is never reported in the literature.

Published
2020
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27. Prevalence of chronic kidney disease in the community using data from OxRen: a UK population-based cohort study

Author

Hirst, Jennifer A, primary, Hill, Nathan, additional, O’Callaghan, Chris A, additional, Lasserson, Daniel, additional, McManus, Richard J, additional, Ogburn, Emma, additional, Mena, José M Ordóñez, additional, Shine, Brian, additional, Taylor, Clare J, additional, Vazquez-Montes, Maria DLA, additional, Yang, Yaling, additional, and Hobbs, FD Richard, additional

Published
2020
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28. Activating Mutations of the G-protein Subunit α 11 Interdomain Interface Cause Autosomal Dominant Hypocalcemia Type 2

Author

Gorvin, Caroline M, primary, Stokes, Victoria J, additional, Boon, Hannah, additional, Cranston, Treena, additional, Glück, Anna K, additional, Bahl, Shailini, additional, Homfray, Tessa, additional, Aung, Theingi, additional, Shine, Brian, additional, Lines, Kate E, additional, Hannan, Fadil M, additional, and Thakker, Rajesh V, additional

Published
2019
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37. Recovery of the Hypothalamo-Pituitary-Adrenal Axis After Transsphenoidal Adenomectomy for Non–ACTH-Secreting Macroadenomas

Author

Pofi, Riccardo, primary, Gunatilake, Sonali, additional, Macgregor, Victoria, additional, Shine, Brian, additional, Joseph, Robin, additional, Grossman, Ashley B, additional, Isidori, Andrea M, additional, Cudlip, Simon, additional, Jafar-Mohammadi, Bahram, additional, Tomlinson, Jeremy W, additional, and Pal, Aparna, additional

Published
2019
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38. The PSA testing dilemma: GPs' reports of consultations with asymptomatic men: a qualitative study

Author

Shine Brian, Bukach Colleen, Rai Tanvi, Watson Eila, Clements Alison, and Austoker Joan

Subjects
Medicine (General), R5-920
Abstract

Abstract Background The National Health Service Prostate Cancer Risk Management Programme (PCRMP) has recommended that screening for prostate cancer is available for asymptomatic men, on the understanding that they have been provided with full and balanced information about the advantages and limitations of the prostate-specific antigen (PSA) test. Guidance has been distributed to all GPs in England and Wales to assist in the provision of information to men. This study aimed to elicit GPs' accounts of their discussions with asymptomatic men who consult with concerns about prostate cancer in order to identify the degree to which the PCRMP guidance was reflected in these consultations. Methods Qualitative interview study. Semi-structured telephone interviews with 21 GPs from 18 GP practices in Oxfordshire. Results All GPs reported undertaking some discussion with asymptomatic men about the PSA test. They described focussing most of the discussion on the false-positive and false-negative rates of the test, and the risks associated with a prostate biopsy. They reported less discussion of the potential for diagnosing indolent cancers, the dilemmas regarding treatment options for localised prostate cancer and the potential benefits of testing. Considerable variation existed between GPs in their accounts of the degree of detail given, and GP's presentation of information appeared to be affected by their personal views of the PSA test. Conclusion The GPs in this study appear to recognise the importance of discussions regarding PSA testing; however, a full and balanced picture of the associated advantages and limitations does not seem to be consistently conveyed. Factors specific to PSA testing which appeared to have an impact on the GPs' discussions were the GP's personal opinions of the PSA test, and the need to counter men's primarily positive views of the benefits of PSA testing. Awareness of the impact of their views on the consultations may help GPs give men a more balanced presentation of the benefits and limitations of the PSA test.

Published
2007
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48. In primary care, is measuring freethyroxine plus thyroid-stimulating hormone to detect hypopituitarism costeffective? A cost utility analysis using Markov chain models.

Author

Shine, Brian, James, Tim, and Adler, Amanda

Abstract

Objective We examined whether it is cost-effective to measure free thyroxine (FT4) in addition to thyrotropin (thyroid-stimulating hormone (TSH)) on all requests for thyroid function tests from primary care on adult patients. Background Hypopituitarism occurs in about 4 people per 100 000 per year. Loss of thyrotropin (TSH) secretion may lead to secondary hypothyroidism with a low TSH and low FT4, and this pattern may help to diagnose hypopituitarism that might otherwise be missed. Design Markov model simulation. Primary outcome measure Incremental costeffectiveness ratio (ICER), the ratio of cost in pounds to benefit in quality-adjusted life years of this strategy. Results The ICER for this strategy was £71 437. Factors with a large influence on the ICER were the utilities of the treated hypopituitary state, the likelihood of going to the general practitioner (GP) and of the GP recognising a hypopituitary patient. The ICER would be below £20 000 at a cost to the user of an FT4 measurement of £0.61. Conclusion With FT4 measurements at their present cost to the user, routine inclusion of FT4 in a thyroid hormone profile is not cost-effective. [ABSTRACT FROM AUTHOR]

Published
2019
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