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Research outputs from the Oncology department at the RD&E.


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    Artificial intelligence - can it be used to outsmart oral cancer?
    (Springer Nature, 2022-03-01) Baniulyte, G.; Ali, K.
    Data Sources Electronic search on PubMed, Cochrane, Scopus, Embase, Google Scholar, Saudi Digital Library and Web of Science, and hand searching carried out for studies published January 2000-March 2021. Language was restricted to English.Study selection Original research studies involving artificial intelligence technology for oral cancer diagnosis and prognosis prediction were considered. The studies had to provide quantitative data of their evaluation analysis. The exclusion criteria were reported. No limit was set on study design.Data extraction and synthesis The initial search yielded 628 articles. Following deduplication, 340 full-text articles were screened. QUADAS-2 tool was used to assess the quality of the included studies regarding diagnostic accuracy.Results A total of 16 studies were included with various study designs: 14 cross-sectional, one cohort and one retrospective study. Six studies reviewed the diagnosis aspect. All studies indicate an overall positive trend of artificial intelligence technology.Conclusions Artificial intelligence appears to have good accuracy in oral cancer diagnosis and its prediction.
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    Associations Between Glycemic Traits and Colorectal Cancer: A Mendelian Randomization Analysis
    (Oxford University Press, 2022-01-20) Murphy, N.; Song, M.; Papadimitriou, N.; Carreras-Torres, R.; Langenberg, C.; Martin, R. M.; Tsilidis, K. K.; Barroso, I.; Chen, J.; Frayling, T.; Bull, C. J.; Vincent, E. E.; Cotterchio, M.; Gruber, S. B.; Pai, R. K.; Newcomb, P. A.; Perez-Cornago, A.; van Duijnhoven, F. J. B.; Van Guelpen, B.; Vodicka, P.; Wolk, A.; Wu, A. H.; Peters, U.; Chan, A. T.; Gunter, M. J.
    BACKGROUND: Glycemic traits-such as hyperinsulinemia, hyperglycemia, and type-2 diabetes-have been associated with higher colorectal cancer risk in observational studies; however, causality of these associations is uncertain. We used Mendelian randomization (MR) to estimate the causal effects of fasting insulin, 2-hour glucose, fasting glucose, glycated hemoglobin (HbA1c), and type-2 diabetes with colorectal cancer. METHODS: Genome-wide association study summary data were used to identify genetic variants associated with circulating levels of fasting insulin (n = 34), 2-hour glucose (n = 13), fasting glucose (n = 70), HbA1c (n = 221), and type-2 diabetes (n = 268). Using two-sample MR, we examined these variants in relation to colorectal cancer risk (48,214 cases and 64,159 controls). RESULTS: In inverse-variance models, higher fasting insulin levels increased colorectal cancer risk (odds ratio [OR] per 1-standard deviation [SD]=1.65, 95% CI = 1.15-2.36). We found no evidence of any effect of 2-hour glucose (OR per 1-SD = 1.02, 95% CI = 0.86-1.21) or fasting glucose (OR per 1-SD = 1.04, 95% CI = 0.88-1.23) concentrations on colorectal cancer risk. Genetic liability to type-2 diabetes (OR per 1-unit increase in log odds = 1.04, 95% CI = 1.01-1.07) and higher HbA1c levels (OR per 1-SD = 1.09, 95% CI = 1.00-1.19) increased colorectal cancer risk, although these findings may have been biased by pleiotropy. Higher HbA1c concentrations increased rectal cancer risk in men (OR per 1-SD = 1.21, 95% CI = 1.05-1.40), but not in women. CONCLUSIONS: Our results support a causal effect of higher fasting insulin, but not glucose traits or type-2 diabetes, on increased colorectal cancer risk. This suggests that pharmacological or lifestyle interventions that lower circulating insulin levels may be beneficial in preventing colorectal tumorigenesis.
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    British Gynaecological Cancer Society (BGCS) uterine cancer guidelines: Recommendations for practice
    (Elsevier, 2021-11-25) Morrison, J.; Balega, J.; Buckley, L.; Clamp, A.; Crosbie, E.; Drew, Y.; Durrant, L.; Forrest, J.; Fotopoulou, C.; Gajjar, K.; Ganesan, R.; Gupta, J.; Hughes, J.; Miles, T.; Moss, E.; Nanthakumar, M.; Newton, C.; Ryan, N.; Walther, A.; Taylor, A.
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    Re-evaluating the diagnostic efficacy of PSA as a referral test to detect clinically significant prostate cancer in contemporary MRI-based image-guided biopsy pathways
    (Sage, 2021-12-01) Lophatananon, Artitaya; Light, Alexander; Burns-Cox, Nicholas; Maccormick, Angus; John, Joseph; Otti, Vanessa; McGrath, John; Archer, Pete; Anning, Jonathan; McCracken, Stuart; Page, Toby; Muir, Ken; Gnanapragasam, Vincent J
    Introduction:Modern image-guided biopsy pathways at diagnostic centres have greatly refined the investigations of men referred with suspected prostate cancer. However, the referral criteria from primary care are still based on historical prostate-specific antigen (PSA) cut-offs and age-referenced thresholds. Here, we tested whether better contemporary pathways and biopsy methods had improved the predictive utility value of PSA referral thresholds.Methods:PSA referral thresholds, age-referenced ranges and PSA density (PSAd) were assessed for positive predictive value (PPV) in detection of clinically significant prostate cancer (csPCa – histological ⩾ Grade Group 2). Data were analysed from men referred to three diagnostics centres who used multi-parametric magnetic resonance imaging (mpMRI)-guided prostate biopsies for disease characterisation. Findings were validated in a separate multicentre cohort.Results:Data from 2767 men were included in this study. The median age, PSA and PSAd were 66.4 years, 7.3 ng/mL and 0.1 ng/mL2, respectively. Biopsy detected csPCa was found in 38.7%. The overall area under the curve (AUC) for PSA was 0.68 which is similar to historical performance. A PSA threshold of ⩾ 3 ng/mL had a PPV of 40.3%, but this was age dependent (PPV: 24.8%, 32.7% and 56.8% in men 50–59 years, 60–69 years and ⩾ 70 years, respectively). Different PSA cut-offs and age-reference ranges failed to demonstrate better performance. PSAd demonstrated improved AUC (0.78 vs 0.68, p < 0.0001) and improved PPV compared to PSA. A PSAd of ⩾ 0.10 had a PPV of 48.2% and similar negative predictive value (NPV) to PSA ⩾ 3 ng/mL and out-performed PSA age-reference ranges. This improved performance was recapitulated in a separate multi-centre cohort (n = 541).Conclusion:The introduction of MRI-based image-guided biopsy pathways does not appear to have altered PSA diagnostic test characteristics to positively detect csPCa. We find no added value to PSA age-referenced ranges, while PSAd offers better PPV and the potential for a single clinically useful threshold (⩾0.10) for all age groups.Level of evidence:IV
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    Gilteritinib for Relapsed Acute Myeloid Leukaemia with FLT3 Mutation during the COVID-19 Pandemic: Real World Experience from the UK National Health Service
    (Blood, 2021-11-05) Othman, Jad; Afzal, Usman; Amofa, Ruebina; Austin, Michael J; Bashford, Alex; Belsham, Edward; Byrne, Jennifer; Coats, Thomas; Dang, Raymond; Dennis, Mike; Dhawan, Saniya; Elliot, Johnathon; Francis, Sebastian; Gallipoli, Paolo; Hodgson, Katherine; Kallmeyer, Charlotte; Jain, Manish; Katsomitrou, Vana; Khan, Anjum; Khwaja, Asim; Kolade, Seye; Krishnamurthy, Pramila; Latif, Annie; Laurie, John; Lim, Michael; Loke, Ching Ting; Manson, Cara; Marshall, Scott R.; Mobashwera, Behnaz; Munisamy, Sreetharan; Murray, Duncan; Murthy, Vidhya; Palanicawandar, Renuka; Saunders, Jamie; Smith, Matthew; Smith, Katherine; Sternberg, Alex; Taussig, David; Taylor, Tom; Freeman, Sylvie D; Craddock, Charles; Dillon, Richard
    BackgroundEarly data suggest that patients undergoing salvage chemotherapy for relapsed or refractory (R/R) acute myeloid leukaemia (AML) have poor outcomes if infected with SARS-CoV-2, and nosocomial transmission has been a major problem worldwide. Gilteritinib is effective in R/R FLT3 mutated AML, is significantly less immunosuppressive and does not require hospital admission, however at the start of the pandemic this was not yet approved for routine use in all countries. In the United Kingdom, the National Health Service (NHS) made gilteritinib available as an emergency measure from late April 2020 to patients aged >16y with R/R FLT3 mutated AML, with the aim of reducing both mortality and healthcare resource use. We report a health-system-wide real world data collection for toxicity and patient outcomes across 27 NHS Hospitals.MethodsEach patient was registered on a central NHS database, with clinicians certifying that their patient met the above criteria. Anonymised data were retrospectively collected by treating physicians. Gilteritinib dose, duration and toxicity information was requested for the first 4 cycles of therapy. Response definitions were as per European Leukaemia Network (ELN) guidelines. A total of 81 patients have been registered on the scheme, with outcomes reported here for those with follow-up information at a data cut on 1st August 2021.ResultsFifty patients were included with a median age of 59y (range 19 - 77) and 50% male. The majority (83%) had an ECOG performance status of 0-1. AML was secondary to a previous haematological disorder in 12%, therapy-related in 4% and de novo in the remaining 84%. The disease was refractory to the last therapy in 38%. Most patients had previously received 1 (65%) or 2 (33%) lines of therapy, including intensive chemotherapy in a majority (86%). A FLT3 inhibitor had previously been administered to 45% and 35% were post allogeneic transplant. The FLT3 mutation was an internal tandem duplication (ITD) in 80% and tyrosine kinase domain (TKD) mutation in 22%. NPM1 mutations were detected in 34%. Next-generation sequencing results were available for 94% of patients, with mutations in IDH1 or IDH2 in 12.5%, ASXL1 in 2%, RUNX1 in 21% and no TP53 mutations.Patients spent a median 3.5 days in hospital in cycle 1, 0 days in cycles 2 and 3 and 1 day in cycle 4. In cycles 1, 2, 3 and 4, the median number of days of grade 4 neutropenia was 18, 7, 7.5, and 6.5 respectively, and the grade 4 thrombocytopenia was 2, 7, 0.5 and 0.5. The composite complete remission (CR) / CR with incomplete haematological recovery (CRi) rate was 27%. MRD data is being collected. The best response was morphological leukaemia free state (MLFS) in 4%, partial remission (PR) in 25% and refractory disease in 38%. The rate of combined CR/CRi did not differ in those with previous exposure to FLT3 inhibitors (23% vs 32%, p=0.6) or with past allogeneic transplant (29% vs 27%, p=0.3). There were no CR/CRi in patients with adverse cytogenetic risk.Median follow-up was 10.5 months (95%CI 7.3 - 12.3) with median overall survival (OS) 6.7 months (95%CI 4.5 - not reached). Mortality at day 30 was 0% and day 60 was 14%. 12-month overall survival was 38%. Patients who achieved a CR/CRi had a 12-month OS of 83%, and for PR this was 35%. Survival did not differ in those with previous FLT3 inhibitor exposure (HR 1.0, p>0.9) or allogeneic transplant (HR 0.63, p=0.3). Seven patients (14%) so far have been bridged with gilteritinib to allogeneic transplant.ConclusionOur data demonstrate that gilteritinib is well tolerated and clinically active in adults with relapsed FLT3 mutated AML. Importantly, during the COVID-19 pandemic, its availability has permitted the great majority of treatment to be delivered as an outpatient with significant resource saving at a time of critically constrained inpatient resources. Patients who achieve CR/CRi have good short-term outcomes and are able to proceed to a potentially curative allogeneic stem cell transplant.Figure 1Figure 1. Belsham: Celgene: Other: meeting attendance; Abbvie: Other: meeting attendance. Byrne: Incyte: Honoraria. Khan: Abbvie: Honoraria; Astellas: Honoraria; Takeda: Honoraria; Jazz: Honoraria; Gilead: Honoraria; Novartis: Honoraria. Khwaja: Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astellas: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Latif: Kite: Consultancy, Honoraria, Speakers Bureau; Jazz: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Astellas: Consultancy, Honoraria, Speakers Bureau; Takeda UK: Speakers Bureau. Loke: Amgen: Honoraria; Daichi Sankyo: Other: Travel Support; Janssen: Honoraria; Novartis: Other: Travel Support; Pfizer: Honoraria. Munisamy: Jazz Pharmaceuticals: Speakers Bureau; Roche: Speakers Bureau. Murthy: Abbvie: Other: support to attend educational conferences.. Smith: Daiichi Sankyo: Speakers Bureau; Pfizer: Speakers Bureau; ARIAD: Honoraria. Craddock: Novartis Pharmaceuticals: Other: Advisory Board ; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding. Dillon: Amgen: Other: Research support (paid to institution); Astellas: Consultancy, Other: Educational Events , Speakers Bureau; Menarini: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Other: Session chair (paid to institution), Speakers Bureau; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: educational events; Jazz: Other: Education events; Shattuck Labs: Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Research Support, Educational Events.