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Bermingham KM, May A, Asnicar F, Capdevila J, Leeming ER, Franks PW, Valdes AM, Wolf J, Hadjigeorgiou G, Delahanty LM, Segata N, Spector TD, Berry SE. Snack quality and snack timing are associated with cardiometabolic blood markers: the ZOE PREDICT study. Eur J Nutr 2024; 63:121-133. [PMID: 37709944 PMCID: PMC10799113 DOI: 10.1007/s00394-023-03241-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 08/16/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND Snacking is a common diet behaviour which accounts for a large proportion of daily energy intake, making it a key determinant of diet quality. However, the relationship between snacking frequency, quality and timing with cardiometabolic health remains unclear. DESIGN Demography, diet, health (fasting and postprandial cardiometabolic blood and anthropometrics markers) and stool metagenomics data were assessed in the UK PREDICT 1 cohort (N = 1002) (NCT03479866). Snacks (foods or drinks consumed between main meals) were self-reported (weighed records) across 2-4 days. Average snacking frequency and quality [snack diet index (SDI)] were determined (N = 854 after exclusions). Associations between snacking frequency, quality and timing with cardiometabolic blood and anthropometric markers were assessed using regression models (adjusted for age, sex, BMI, education, physical activity level and main meal quality). RESULTS Participants were aged (mean, SD) 46.1 ± 11.9 years, had a mean BMI of 25.6 ± 4.88 kg/m2 and were predominantly female (73%). 95% of participants were snackers (≥ 1 snack/day; n = 813); mean daily snack intake was 2.28 snacks/day (24 ± 16% of daily calories; 203 ± 170 kcal); and 44% of participants were discordant for meal and snack quality. In snackers, overall snacking frequency and quantity of snack energy were not associated with cardiometabolic risk markers. However, lower snack quality (SDI range 1-11) was associated with higher blood markers, including elevated fasting triglycerides (TG (mmol/L) β; - 0.02, P = 0.02), postprandial TGs (6hiAUC (mmol/L.s); β; - 400, P = 0.01), fasting insulin (mIU/L) (β; - 0.15, P = 0.04), insulin resistance (HOMA-IR; β; - 0.04, P = 0.04) and hunger (scale 0-100) (β; - 0.52, P = 0.02) (P values non-significant after multiple testing adjustments). Late-evening snacking (≥ 9 pm; 31%) was associated with lower blood markers (HbA1c; 5.54 ± 0.42% vs 5.46 ± 0.28%, glucose 2hiAUC; 8212 ± 5559 vs 7321 ± 4928 mmol/L.s, P = 0.01 and TG 6hiAUC; 11,638 ± 8166 vs 9781 ± 6997 mmol/L.s, P = 0.01) compared to all other snacking times (HbA1c remained significant after multiple testing). CONCLUSION Snack quality and timing of consumption are simple diet features which may be targeted to improve diet quality, with potential health benefits. CLINICAL TRIAL REGISTRY NUMBER AND WEBSITE NCT03479866, https://clinicaltrials.gov/ct2/show/NCT03479866?term=NCT03479866&draw=2&rank=1.
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Affiliation(s)
- Kate M Bermingham
- Department of Nutritional Sciences, King's College London, London, UK
- ZOE Ltd, London, UK
| | | | | | | | - Emily R Leeming
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Paul W Franks
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Ana M Valdes
- School of Medicine, University of Nottingham, Nottingham, UK
- Nottingham NIHR Biomedical Research Centre, Nottingham, UK
| | | | | | - Linda M Delahanty
- Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sarah E Berry
- Department of Nutritional Sciences, King's College London, London, UK.
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Capdevila J, Hernando J, Teule A, Lopez C, Garcia-Carbonero R, Benavent M, Custodio A, Garcia-Alvarez A, Cubillo A, Alonso V, Carmona-Bayonas A, Alonso-Gordoa T, Crespo G, Jimenez-Fonseca P, Blanco M, Viudez A, La Casta A, Sevilla I, Segura A, Llanos M, Landolfi S, Nuciforo P, Manzano JL. Durvalumab plus tremelimumab for the treatment of advanced neuroendocrine neoplasms of gastroenteropancreatic and lung origin. Nat Commun 2023; 14:2973. [PMID: 37221181 DOI: 10.1038/s41467-023-38611-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 05/10/2023] [Indexed: 05/25/2023] Open
Abstract
Single immune checkpoint blockade in advanced neuroendocrine neoplasms (NENs) shows limited efficacy; dual checkpoint blockade may improve treatment activity. Dune (NCT03095274) is a non-randomized controlled multicohort phase II clinical trial evaluating durvalumab plus tremelimumab activity and safety in advanced NENs. This study included 123 patients presenting between 2017 and 2019 with typical/atypical lung carcinoids (Cohort 1), G1/2 gastrointestinal (Cohort 2), G1/2 pancreatic (Cohort 3) and G3 gastroenteropancreatic (GEP) (Cohort 4) NENs; who progressed to standard therapies. Patients received 1500 mg durvalumab and 75 mg tremelimumab for up to 13 and 4 cycles (every 4 weeks), respectively. The primary objective was the 9-month clinical benefit rate (CBR) for cohorts 1-3 and 9-month overall survival (OS) rate for Cohort 4. Secondary endpoints included objective response rate, duration of response, progression-free survival according to irRECIST, overall survival, and safety. Correlation of PD-L1 expression with efficacy was exploratory. The 9-month CBR was 25.9%/35.5%/25% for Cohorts 1, 2, and 3 respectively. The 9-month OS rate for Cohort 4 was 36.1%, surpassing the futility threshold. Benefit in Cohort 4 was observed regardless of differentiation and Ki67 levels. PD-L1 combined scores did not correlate with treatment activity. Safety profile was consistent with that of prior studies. In conclusion, durvalumab plus tremelimumab is safe in NENs and shows modest survival benefit in G3 GEP-NENs; with one-third of these patients experiencing a prolonged OS.
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Affiliation(s)
- J Capdevila
- Medical Oncology Department, Vall Hebron University Hospital, Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain.
- Medical Oncology Department, IOB-Quiron-Teknon, Barcelona, Spain.
| | - J Hernando
- Medical Oncology Department, Vall Hebron University Hospital, Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - A Teule
- Medical Oncology Department, Institut Català d'Oncologia (ICO) - IDIBELL L'Hospitalet del Llobregat, L'Hospitalet de Llobregat, Spain
| | - C Lopez
- Medical Oncology Department, Hospital Universitario Marqués de Valdecilla, IDIVAL, Santander, Spain
| | - R Garcia-Carbonero
- Medical Oncology Department, Hospital Universitario 12 de Octubre, Imas12, UCM, CNIO, Madrid, Spain
| | - M Benavent
- Medical Oncology Department, University Hospital Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS), Seville, Spain
| | - A Custodio
- Medical Oncology Department, Hospital Universitario La Paz, Madrid, Spain
| | - A Garcia-Alvarez
- Medical Oncology Department, Vall Hebron University Hospital, Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - A Cubillo
- Medical Oncology Department, Hospital Universitario HM Sanchinarro, Madrid, Spain
| | - V Alonso
- Medical Oncology Department, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria de Aragón (IISA), Zaragoza, Spain
| | - A Carmona-Bayonas
- Hematology and Medical Oncology Department, Hospital Universitario Morales Meseguer, UMU, IMIB, Murcia, Spain
| | - T Alonso-Gordoa
- Medical Oncology, Hospital Universitario Ramón y Cajal, Madrid, Spain
| | - G Crespo
- Medical Oncology Department, Complejo Asistencial Universitario de Burgos, Burgos, Spain
| | - P Jimenez-Fonseca
- Medical Oncology Department, Hospital Universitario Central de Asturias, ISPA, Oviedo, Spain
| | - M Blanco
- Medical Oncology Department, Hospital Universitario Gregorio Marañon, Madrid, Spain
| | - A Viudez
- Medical Oncology Department, Hospital Universitario de Navarra, Pamplona, Spain
| | - A La Casta
- Medical Oncology Department, Hospital Universitario Donostia, San Sebastián, Spain
| | - I Sevilla
- Medical Oncology Department, Investigación Clínica y Traslacional en Cáncer/Instituto de Investigaciones Biomédicas de Málaga (IBIMA)/Hospitales Universitarios Regional y Virgen de la Victoria de Málaga, Málaga, Spain
| | - A Segura
- Medical Oncology Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain
| | - M Llanos
- Medical Oncology Department, Hospital Universitario de Canarias, San Cristobal de la Laguna, Spain
| | - S Landolfi
- Pathology Department, Vall Hebron University Hospital, CIBERONC, Barcelona, Spain
| | - P Nuciforo
- Molecular Oncology Group. Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - J L Manzano
- Medical Oncology Department, Institut Català d'Oncologia (ICO) - Badalona, Hospital Germans Trias i Pujol, Badalona, Spain
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Dijkstra EA, Zwart WH, Nilsson PJ, Putter H, Roodvoets AGH, Meershoek-Klein Kranenbarg E, Frödin JE, Nygren P, Østergaard L, Kersten C, Verbiené I, Cervantes A, Hendriks MP, Capdevila J, Edhemovic I, van de Velde CJH, Marijnen CAM, van Etten B, Hospers GAP, Glimelius B. The value of post-operative chemotherapy after chemoradiotherapy in patients with high-risk locally advanced rectal cancer-results from the RAPIDO trial. ESMO Open 2023; 8:101158. [PMID: 36871393 PMCID: PMC10163161 DOI: 10.1016/j.esmoop.2023.101158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 01/20/2023] [Accepted: 02/02/2023] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND Pre-operative chemoradiotherapy (CRT) rather than radiotherapy (RT) has resulted in fewer locoregional recurrences (LRRs), but no decrease in distant metastasis (DM) rate for patients with locally advanced rectal cancer (LARC). In many countries, patients receive post-operative chemotherapy (pCT) to improve oncological outcomes. We investigated the value of pCT after pre-operative CRT in the RAPIDO trial. PATIENTS AND METHODS Patients were randomised between experimental (short-course RT, chemotherapy and surgery) and standard-of-care treatment (CRT, surgery and pCT depending on hospital policy). In this substudy, we compared curatively resected patients from the standard-of-care group who received pCT (pCT+ group) with those who did not (pCT- group). Subsequently, patients from the pCT+ group who received at least 75% of the prescribed chemotherapy cycles (pCT ≥75% group) were compared with patients who did not receive pCT (pCT-/- group). By propensity score stratification (PSS), we adjusted for the following unbalanced confounders: age, clinical extramural vascular invasion, distance to the anal verge, ypT stage, ypN stage, residual tumour, serious adverse event (SAE) and/or readmission within 6 weeks after surgery and SAE related to pre-operative CRT. Cumulative probability of disease-free survival (DFS), DM, LRR and overall survival (OS) was analysed by Cox regression. RESULTS In total, 396/452 patients had a curative resection. The number of patients in the pCT+, pCT >75%, pCT- and pCT-/- groups was 184, 112, 154 and 149, respectively. The PSS-adjusted analyses for all endpoints demonstrated hazard ratios between approximately 0.7 and 0.8 (pCT+ versus pCT-), and 0.5 and 0.8 (pCT ≥75% versus pCT-/-). However, all 95% confidence intervals included 1. CONCLUSIONS These data suggest a benefit of pCT after pre-operative CRT for patients with high-risk LARC, with approximately 20%-25% improvement in DFS and OS and 20%-25% risk reductions in DM and LRR. Compliance with pCT additionally reduces or improves all endpoints by 10%-20%. However, differences are not statistically significant.
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Affiliation(s)
- E A Dijkstra
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - W H Zwart
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - P J Nilsson
- Department of Surgery, Karolinska University Hospital, Stockholm, Sweden
| | - H Putter
- Departments of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, the Netherlands
| | - A G H Roodvoets
- Departments of Surgery, Leiden University Medical Center, Leiden, the Netherlands
| | | | - J E Frödin
- Department of Oncology-Pathology, Karolinska University Hospital, Uppsala
| | - P Nygren
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - L Østergaard
- Department of Clinical Medicine, Aalborg University Hospital, Aalborg, Denmark
| | - C Kersten
- Department of Research, Sørlandet Hospital Trust, Kristiansand, Norway
| | - I Verbiené
- Department of Oncology, Uppsala University, Uppsala, Sweden
| | - A Cervantes
- Department of Medical Oncology, Biomedical Research Institute Incliva, University of Valencia, Valencia, Spain
| | - M P Hendriks
- Department of Medical Oncology, Northwest Clinics, Alkmaar, the Netherlands
| | - J Capdevila
- Department of Medical Oncology, Vall Hebron Institute of Oncology (VHIO), Vall Hebron University Hospital. Autonomous University of Barcelona (UAB), Barcelona, Spain
| | - I Edhemovic
- Department of Surgical Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia
| | - C J H van de Velde
- Departments of Surgery, Leiden University Medical Center, Leiden, the Netherlands
| | - C A M Marijnen
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam; Department of Radiation Oncology, Leiden University Medical Center, Leiden
| | - B van Etten
- Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - G A P Hospers
- Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - B Glimelius
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
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Munuera A, Solans M, Novo S, Capdevila J, Faura AG, García F, Marquès B, Castelló C, Teijón ML. Self-reparation signs in embryo development. Reprod Biomed Online 2022. [DOI: 10.1016/j.rbmo.2022.08.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/07/2022]
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Salazar R, Tafuto S, Krogh M, Teule A, Garcia-Carbonero R, Klumpen H, Cremer B, Sevilla I, Eriksson B, Tabaksblat E, Metges JP, Reed N, Schrader J, Navarro V, Valentí V, Hernando J, Colao A, Vestermark L, Carnaghi C, Capdevila J. LBA45 Randomized open label phase III study comparing the efficacy and safety of everolimus followed by chemotherapy (CT) with streptozotocin (STZ)-5FU upon progression or the reverse sequence, in advanced progressive panNETs: The SEQTOR study (GETNE 1206). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.08.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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Rao S, Anandappa G, Capdevila J, Dahan L, Evesque L, Kim S, Saunders MP, Gilbert DC, Jensen LH, Samalin E, Spindler KL, Tamberi S, Demols A, Guren MG, Arnold D, Fakih M, Kayyal T, Cornfeld M, Tian C, Catlett M, Smith M, Spano JP. A phase II study of retifanlimab (INCMGA00012) in patients with squamous carcinoma of the anal canal who have progressed following platinum-based chemotherapy (POD1UM-202). ESMO Open 2022; 7:100529. [PMID: 35816951 PMCID: PMC9463376 DOI: 10.1016/j.esmoop.2022.100529] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 06/06/2022] [Indexed: 02/07/2023] Open
Abstract
Background Locally advanced or metastatic squamous carcinoma of the anal canal (SCAC) has poor prognosis following platinum-based chemotherapy. Retifanlimab (INCMGA00012), a humanized monoclonal antibody targeting programmed death protein-1 (PD-1), demonstrated clinical activity across a range of solid tumors in clinical trials. We present results from POD1UM-202 (NCT03597295), an open-label, single-arm, multicenter, phase II study evaluating retifanlimab in patients with previously treated advanced or metastatic SCAC. Patients and methods Patients ≥18 years of age had measurable disease and had progressed following, or were ineligible for, platinum-based therapy. Retifanlimab 500 mg was administered intravenously every 4 weeks. The primary endpoint was overall response rate (ORR) by independent central review. Secondary endpoints were duration of response (DOR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety. Results Overall, 94 patients were enrolled. At a median follow-up of 7.1 months (range, 0.9-19.4 months), ORR was 13.8% [95% confidence interval (CI) 7.6% to 22.5%], with one complete response (1.1%) and 12 partial responses (12.8%). Responses were observed regardless of human immunodeficiency virus or human papillomavirus status, programmed death ligand 1 (PD-L1) expression, or liver metastases. Stable disease was observed in 33 patients (35.1%) for a DCR of 48.9% (95% CI 38.5% to 59.5%). Median DOR was 9.5 months (range, 5.6 months-not estimable). Median (95% CI) PFS and OS were 2.3 (1.9-3.6) and 10.1 (7.9-not estimable) months, respectively. Retifanlimab safety in this population was consistent with previous experience for the PD-(L)1 inhibitor class. Conclusions Retifanlimab demonstrated clinically meaningful and durable antitumor activity, and an acceptable safety profile in patients with previously treated locally advanced or metastatic SCAC who have progressed on or are intolerant to platinum-based chemotherapy. Retifanlimab (PD-1 inhibitor) monotherapy demonstrated encouraging results in patients with platinum-refractory SCAC. Clinically meaningful antitumor activity was reported with ORR of 13.8% and stable disease in 35.1%, for a DCR of 48.9%. Observed responses in advanced SCAC were durable (median 9.5 months). Acceptable safety profile consistent with that reported for the PD-(L)1 inhibitor class. Promising results warrant further investigation of retifanlimab in advanced SCAC as well as earlier stages of disease.
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Affiliation(s)
- S Rao
- The Royal Marsden, London, UK.
| | | | - J Capdevila
- Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology (VHIO), Teknon-IOB, Barcelona, Spain
| | - L Dahan
- Hôpital de la Timone, Marseille, France
| | - L Evesque
- Department of Medical Oncology, Centre Antoine Lacassagne, Nice, France
| | - S Kim
- Centre Hospitalier Régional Universitaire de Besançon, Besançon, France
| | | | - D C Gilbert
- Sussex Cancer Centre, Royal Sussex County Hospital, Brighton, UK
| | - L H Jensen
- University Hospital of Southern Denmark, Vejle, Denmark
| | - E Samalin
- Department of Digestive Oncology, Montpellier Cancer Institute (ICM), Montpellier University, Montpellier, France
| | | | - S Tamberi
- Department of Oncology/Haematology, AUSL Romagna Oncology Unit Faenza Hospital (RA), Faenza, Italy
| | - A Demols
- Department of Gastroenterology and GI Oncology, CUB Hôpital Erasme, Université Libre de Bruxelles, Anderlecht, Belgium
| | - M G Guren
- Oslo University Hospital and University of Oslo, Oslo, Norway
| | - D Arnold
- Asklepios Tumorzentrum Hamburg, AK Altona, Hamburg, Germany
| | - M Fakih
- City of Hope Comprehensive Cancer Center, Duarte, USA
| | - T Kayyal
- Renovatio Clinical, Houston, USA
| | | | - C Tian
- Incyte Corporation, Wilmington, USA
| | | | - M Smith
- Incyte Corporation, Wilmington, USA
| | - J-P Spano
- APHP-Sorbonne University-IUC, Paris, France
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Menni C, May A, Polidori L, Louca P, Wolf J, Capdevila J, Hu C, Ourselin S, Steves CJ, Valdes AM, Spector TD. COVID-19 vaccine waning and effectiveness and side-effects of boosters: a prospective community study from the ZOE COVID Study. The Lancet Infectious Diseases 2022; 22:1002-1010. [PMID: 35405090 PMCID: PMC8993156 DOI: 10.1016/s1473-3099(22)00146-3] [Citation(s) in RCA: 155] [Impact Index Per Article: 77.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 02/18/2022] [Accepted: 02/18/2022] [Indexed: 12/11/2022]
Abstract
Background With the surge of new SARS-CoV-2 variants, countries have begun offering COVID-19 vaccine booster doses to high-risk groups and, more recently, to the adult population in general. However, uncertainty remains over how long primary vaccination series remain effective, the ideal timing for booster doses, and the safety of heterologous booster regimens. We aimed to investigate COVID-19 primary vaccine series effectiveness and its waning, and the safety and effectiveness of booster doses, in a UK community setting. Methods We used SARS-CoV-2 positivity rates in individuals from a longitudinal, prospective, community-based study (ZOE COVID Study), in which data were self-reported through an app, to assess the effectiveness of three COVID-19 vaccines (ChAdOx1 nCov19 [Oxford-AstraZeneca], BNT162b2 [Pfizer-BioNtech], and mRNA1273 [Moderna]) against infection in the 8 months after completion of primary vaccination series. In individuals receiving boosters, we investigated vaccine effectiveness and reactogenicity, by assessing 16 self-reported systemic and localised side-effects. We used multivariate Poisson regression models adjusting for confounders to estimate vaccine effectiveness. Findings We included 620 793 participants who received two vaccine doses (204 731 [33·0%] received BNT162b2, 405 239 [65·3%] received ChAdOx1 nCoV-19, and 10 823 [1·7%] received mRNA-1273) and subsequently had a SARS-CoV-2 test result between May 23 (chosen to exclude the period of alpha [B.1.1.7] variant dominance) and Nov 23, 2021. 62 172 (10·0%) vaccinated individuals tested positive for SARS-CoV-2 and were compared with 40 345 unvaccinated controls (6726 [16·7%] of whom tested positive). Vaccine effectiveness waned after the second dose: at 5 months, BNT162b2 effectiveness was 82·1% (95% CI 81·3–82·9), ChAdOx1 nCoV-19 effectiveness was 75·7% (74·9–76·4), and mRNA-1273 effectiveness was 84·3% (81·2–86·9). Vaccine effectiveness decreased more among individuals aged 55 years or older and among those with comorbidities. 135 932 individuals aged 55 years or older received a booster (2123 [1·6%] of whom tested positive). Vaccine effectiveness for booster doses in 0–3 months after BNT162b2 primary vaccination was higher than 92·5%, and effectiveness for heterologous boosters after ChAdOx1 nCoV-19 was at least 88·8%. For the booster reactogenicity analysis, in 317 011 participants, the most common systemic symptom was fatigue (in 31 881 [10·1%] participants) and the most common local symptom was tenderness (in 187 767 [59·2%]). Systemic side-effects were more common for heterologous schedules (32 632 [17·9%] of 182 374) than for homologous schedules (17 707 [13·2%] of 134 637; odds ratio 1·5, 95% CI 1·5–1·6, p<0·0001). Interpretation After 5 months, vaccine effectiveness remained high among individuals younger than 55 years. Booster doses restore vaccine effectiveness. Adverse reactions after booster doses were similar to those after the second dose. Homologous booster schedules had fewer reported systemic side-effects than heterologous boosters. Funding Wellcome Trust, ZOE, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, Medical Research Council
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Kläser K, Molteni E, Graham M, Canas LS, Österdahl MF, Antonelli M, Chen L, Deng J, Murray B, Kerfoot E, Wolf J, May A, Fox B, Capdevila J, Modat M, Hammers A, Spector TD, Steves CJ, Sudre CH, Ourselin S, Duncan EL. COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2: a prospective observational cohort study. Sci Rep 2022; 12:10904. [PMID: 35764879 PMCID: PMC9240087 DOI: 10.1038/s41598-022-14016-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 05/31/2022] [Indexed: 01/07/2023] Open
Abstract
The Delta (B.1.617.2) variant was the predominant UK circulating SARS-CoV-2 strain between May and December 2021. How Delta infection compares with previous variants is unknown. This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly the predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) the predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. 3581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta versus Alpha infection (including fever, sore throat, and headache) and some vice versa (dyspnoea). Symptom burden in the first week was higher with Delta versus Alpha infection; however, the odds of any given symptom lasting ≥ 7 days was either lower or unchanged. Illness duration ≥ 28 days was lower with Delta versus Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.49) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly reduced the risk of Delta infection (by 69-84%). We conclude that COVID-19 from Delta or Alpha infections is similar. The Delta variant is more transmissible than Alpha; however, current vaccines showed good efficacy against disease. This research framework can be useful for future comparisons with new emerging variants.
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Affiliation(s)
- Kerstin Kläser
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Mark Graham
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Liane S Canas
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Marc F Österdahl
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital Campus, 3rd Floor South Wing Block D, Westminster Bridge Road, London, SE1 7EH, UK
- Department of Aging and Health, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Michela Antonelli
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Liyuan Chen
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Jie Deng
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Benjamin Murray
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Eric Kerfoot
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | | | | | | | | | - Marc Modat
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- King's College London & Guy's and St Thomas' PET Centre, London, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital Campus, 3rd Floor South Wing Block D, Westminster Bridge Road, London, SE1 7EH, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital Campus, 3rd Floor South Wing Block D, Westminster Bridge Road, London, SE1 7EH, UK
- Department of Aging and Health, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Unit for Lifelong Health and Ageing, Department of Population Health Sciences, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Emma L Duncan
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital Campus, 3rd Floor South Wing Block D, Westminster Bridge Road, London, SE1 7EH, UK.
- Department of Endocrinology, Guy's and St Thomas' NHS Foundation Trust, London, UK.
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Esteban Villarrubia J, Hernando J, Gómez Mugarza P, García Álvarez A, Torres Jiménez J, Orejana Martín I, Alonso Orduña V, Gómez-Puerto D, Álvarez Ballesteros P, Polo E, López D, Martínez Delfrade Í, López Roldán B, Roca M, Reguera Puertas P, Barriendos Sanz S, Benini L, Ferreiro Monteagudo R, Monreal Cepero M, Campos Ramírez S, Guillén-Ponce C, Capdevila J. P-69 Anal squamous cell carcinoma (ASCC) outcomes in clinical practice: From localized to metastatic setting. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.04.159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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10
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Gómez-Puerto D, Benini L, Hernando J, García Álvarez A, Vega-Cano S, Molina Lores G, Yaringaño J, López D, Salva de Torres C, Ucha Hermida J, Bueno S, Navalpotro B, Roca M, Vallrivera Valls F, Martí Gallostra M, Kraft M, Sanchez Garcia J, Solis A, Marinello F, Capdevila J, Espín Basany E. P-149 Impact of COVID-19 pandemic and total neoadjuvant therapy (TNT) implementation in pathological complete response (pCR) rates in patients (pts) with locally advanced rectal cancer (LARC). Ann Oncol 2022. [PMCID: PMC9250155 DOI: 10.1016/j.annonc.2022.04.239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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11
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Menni C, Valdes AM, Polidori L, Antonelli M, Penamakuri S, Nogal A, Louca P, May A, Figueiredo JC, Hu C, Molteni E, Canas L, Österdahl MF, Modat M, Sudre CH, Fox B, Hammers A, Wolf J, Capdevila J, Chan AT, David SP, Steves CJ, Ourselin S, Spector TD. Symptom prevalence, duration, and risk of hospital admission in individuals infected with SARS-CoV-2 during periods of omicron and delta variant dominance: a prospective observational study from the ZOE COVID Study. Lancet 2022; 399:1618-1624. [PMID: 35397851 PMCID: PMC8989396 DOI: 10.1016/s0140-6736(22)00327-0] [Citation(s) in RCA: 416] [Impact Index Per Article: 208.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 02/14/2022] [Accepted: 02/15/2022] [Indexed: 01/08/2023]
Abstract
BACKGROUND The SARS-CoV-2 variant of concern, omicron, appears to be less severe than delta. We aim to quantify the differences in symptom prevalence, risk of hospital admission, and symptom duration among the vaccinated population. METHODS In this prospective longitudinal observational study, we collected data from participants who were self-reporting test results and symptoms in the ZOE COVID app (previously known as the COVID Symptoms Study App). Eligible participants were aged 16-99 years, based in the UK, with a body-mass index between 15 and 55 kg/m2, had received at least two doses of any SARS-CoV-2 vaccine, were symptomatic, and logged a positive symptomatic PCR or lateral flow result for SARS-CoV-2 during the study period. The primary outcome was the likelihood of developing a given symptom (of the 32 monitored in the app) or hospital admission within 7 days before or after the positive test in participants infected during omicron prevalence compared with those infected during delta prevalence. FINDINGS Between June 1, 2021, and Jan 17, 2022, we identified 63 002 participants who tested positive for SARS-CoV-2 and reported symptoms in the ZOE app. These patients were matched 1:1 for age, sex, and vaccination dose, across two periods (June 1 to Nov 27, 2021, delta prevalent at >70%; n=4990, and Dec 20, 2021, to Jan 17, 2022, omicron prevalent at >70%; n=4990). Loss of smell was less common in participants infected during omicron prevalence than during delta prevalence (16·7% vs 52·7%, odds ratio [OR] 0·17; 95% CI 0·16-0·19, p<0·001). Sore throat was more common during omicron prevalence than during delta prevalence (70·5% vs 60·8%, 1·55; 1·43-1·69, p<0·001). There was a lower rate of hospital admission during omicron prevalence than during delta prevalence (1·9% vs 2·6%, OR 0·75; 95% CI 0·57-0·98, p=0·03). INTERPRETATION The prevalence of symptoms that characterise an omicron infection differs from those of the delta SARS-CoV-2 variant, apparently with less involvement of the lower respiratory tract and reduced probability of hospital admission. Our data indicate a shorter period of illness and potentially of infectiousness which should impact work-health policies and public health advice. FUNDING Wellcome Trust, ZOE, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, and Medical Research Council.
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Affiliation(s)
- Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Ana M Valdes
- Nottingham NIHR Biomedical Research Centre at the School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Michela Antonelli
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | - Ana Nogal
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Panayiotis Louca
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Jane C Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles CA, USA
| | | | - Erika Molteni
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Liane Canas
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc F Österdahl
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK; Department of Ageing and Health, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Carole H Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | | | - Alexander Hammers
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; King's College London & Guy's and St Thomas' PET Centre, London, UK
| | | | | | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Sean P David
- NorthShore University Health System & University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK; Department of Ageing and Health, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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12
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Graham MS, May A, Varsavsky T, Sudre CH, Murray B, Kläser K, Antonelli M, Canas LS, Molteni E, Modat M, Cardoso MJ, Drew DA, Nguyen LH, Rader B, Hu C, Capdevila J, Hammers A, Chan AT, Wolf J, Brownstein JS, Spector TD, Ourselin S, Steves CJ, Astley CM. Knowledge barriers in a national symptomatic-COVID-19 testing programme. PLOS Glob Public Health 2022; 2:e0000028. [PMID: 36962066 PMCID: PMC10022193 DOI: 10.1371/journal.pgph.0000028] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 11/24/2021] [Indexed: 11/18/2022]
Abstract
Symptomatic testing programmes are crucial to the COVID-19 pandemic response. We sought to examine United Kingdom (UK) testing rates amongst individuals with test-qualifying symptoms, and factors associated with not testing. We analysed a cohort of untested symptomatic app users (N = 1,237), nested in the Zoe COVID Symptom Study (Zoe, N = 4,394,948); and symptomatic respondents who wanted, but did not have a test (N = 1,956), drawn from a University of Maryland survey administered to Facebook users (The Global COVID-19 Trends and Impact Survey [CTIS], N = 775,746). The proportion tested among individuals with incident test-qualifying symptoms rose from ~20% to ~75% from April to December 2020 in Zoe. Testing was lower with one vs more symptoms (72.9% vs 84.6% p<0.001), or short vs long symptom duration (69.9% vs 85.4% p<0.001). 40.4% of survey respondents did not identify all three test-qualifying symptoms. Symptom identification decreased for every decade older (OR = 0.908 [95% CI 0.883-0.933]). Amongst symptomatic UMD-CTIS respondents who wanted but did not have a test, not knowing where to go was the most cited factor (32.4%); this increased for each decade older (OR = 1.207 [1.129-1.292]) and for every 4-years fewer in education (OR = 0.685 [0.599-0.783]). Despite current UK messaging on COVID-19 testing, there is a knowledge gap about when and where to test, and this may be contributing to the ~25% testing gap. Risk factors, including older age and less education, highlight potential opportunities to tailor public health messages. The testing gap may be ever larger in countries that do not have extensive, free testing, as the UK does.
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Affiliation(s)
- Mark S Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Anna May
- Zoe Global Limited, London, United Kingdom
| | - Thomas Varsavsky
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Carole H Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
- Department of Population Science and Experimental Medicine, MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom
- Department of Computer Science, Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Benjamin Murray
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Kerstin Kläser
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Michela Antonelli
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Liane S Canas
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Erika Molteni
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - M Jorge Cardoso
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - David A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Long H Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Benjamin Rader
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States of America
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States of America
| | | | | | - Alexander Hammers
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | | | - John S Brownstein
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States of America
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Christina M Astley
- Computational Epidemiology Lab, Boston Children's Hospital, Boston, MA, United States of America
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, United States of America
- Broad Institute of Harvard and MIT, Cambridge, MA, United States of America
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13
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Merino J, Joshi AD, Nguyen LH, Leeming ER, Mazidi M, Drew DA, Gibson R, Graham MS, Lo CH, Capdevila J, Murray B, Hu C, Selvachandran S, Hammers A, Bhupathiraju SN, Sharma SV, Sudre C, Astley CM, Chavarro JE, Kwon S, Ma W, Menni C, Willett WC, Ourselin S, Steves CJ, Wolf J, Franks PW, Spector TD, Berry S, Chan AT. Diet quality and risk and severity of COVID-19: a prospective cohort study. Gut 2021; 70:2096-2104. [PMID: 34489306 PMCID: PMC8500931 DOI: 10.1136/gutjnl-2021-325353] [Citation(s) in RCA: 105] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 08/19/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Poor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation. DESIGN We used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively. RESULTS Over 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation. CONCLUSIONS A diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.
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Affiliation(s)
- Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Amit D Joshi
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Long H Nguyen
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Emily R Leeming
- Department of Twin Research, King's College London, London, UK
| | - Mohsen Mazidi
- Department of Twin Research, King's College London, London, UK
| | - David A Drew
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Rachel Gibson
- Department of Nutritional Sciences, King's College London, London, UK
| | - Mark S Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Chun-Han Lo
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Benjamin Murray
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | | | - Alexander Hammers
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- King's College London & Guy's and St Thomas' PET Centre, King's College London, London, UK
| | - Shilpa N Bhupathiraju
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Shreela V Sharma
- Department of Epidemiology, Human Genetics, and Environmental Sciences, UT Health School of Public Health, Houston, Texas, USA
| | - Carole Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Christina M Astley
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of Endocrinology & Computational Epidemiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jorge E Chavarro
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sohee Kwon
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Wenjie Ma
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Cristina Menni
- Department of Twin Research, King's College London, London, UK
| | - Walter C Willett
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research, King's College London, London, UK
| | | | - Paul W Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Lund, Sweden
| | - Timothy D Spector
- Department of Nutritional Sciences, King's College London, London, UK
| | - Sarah Berry
- Department of Nutritional Sciences, King's College London, London, UK
| | - Andrew T Chan
- Clinical and Translational Epidemiological Unit, Massachusetts General Hospital, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Grande E, Garcia-Carbonero R, Teule A, Benavent Viñuales M, Jimenez-Fonseca P, Molina-Cerrillo J, López C, Custodio A, Hierro C, Gallego J, Alonso V, Carmona-Bayonas A, Llanos M, Sevilla I, Hernando J, Lista F, Antón Pascual B, Ruffinelli J, Gallego Jiménez I, Capdevila J. 575TiP Cabozantinib plus atezolizumab in advanced and progressive neoplasms of the endocrine system: A multicohort phase II trial (CABATEN trial / GETNE-T1914). Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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Baudin E, Horsch D, Singh S, Caplin M, Ferone D, Wolin E, Capdevila J, Buikhuisen W, Raderer M, Dansin E, Grohe C, Houchard A, Truong Thanh XM, Reidy-Lagunes D. 1096O Lanreotide autogel/depot (LAN) in patients with advanced bronchopulmonary (BP) neuroendocrine tumors (NETs): Results from the phase III SPINET study. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.178] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Garcia-Carbonero R, Benavent M, Jiménez Fonseca P, Castellano D, Alonso-Gordoa T, Teulé A, Custodio A, Tafuto S, La Casta A, Spada F, López C, Ibrahim T, Silva MV, Iranzo V, García-Alfonso P, González-Flores E, Grande E, Crespo G, Carmona-Bayonas A, Capdevila J. 1097O The AXINET trial (GETNE1107): Axitinib plus octreotide LAR improves PFS by blinded central radiological assessment vs placebo plus octreotide LAR in G1-2 extrapancreatic NETs. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.179] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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Riesco-Martinez M, Capdevila J, Alonso V, Jimenez-Fonseca P, Teule A, Grande E, Sevilla I, Benavent Viñuales M, Alonso-Gordoa T, Custodio A, Hernando J, Polo E, Castillo Trujillo O, Garcia-Carbonero R. 1098O Nivolumab plus platinum-doublet chemotherapy as first-line therapy in unresectable, locally advanced or metastatic G3 neuroendocrine Neoplasms (NENs) of the gastroenteropancreatic (GEP) tract or unknown (UK) origin: Preliminary results from the phase II NICE-NEC trial (GETNE T1913). Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Aparicio J, Manrique AV, Capdevila J, Boza FM, Galván P, Richart P, Oliveres H, Paez D, Hernando J, Serrano SG, Vera R, Hernandez X, Gallego RA, Riesco-Martinez M, García de Albeniz X, Maurel J. 416P Randomized phase II trial of second-line FOLFIRI-panitumumab vs FOLFIRI alone in Ras wild type (wt) metastatic colorectal cancer (mCRC) patients beyond progression to first-line FOLFOX-panitumumab: BEYOND study (GEMCAD 17-01). Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Capdevila J, Robinson B, Sherman S, Jarzab B, Lin CC, Vaisman F, Hoff A, Hitre E, Bowles D, Sen S, Patel P, Oliver J, Keam B, Brose M. LBA67 Cabozantinib versus placebo in patients with radioiodine-refractory differentiated thyroid cancer who have progressed after prior VEGFR-targeted therapy: Updated results from the phase III COSMIC-311 trial and prespecified subgroup analyses by prior therapy. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.2148] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Valdivia A, Salva F, Ros J, Baraibar I, Argiles Martinez G, Saoudi Gonzalez N, Garcia A, Mulet Margalef N, Cuadra Urteaga J, Capdevila J, Salud Salvia M, Paez D, Casado E, Comas R, Ruiz-Pace F, Villacampa Javierre G, Acosta Eyzaguirre D, Dienstmann R, Elez Fernandez M, Tabernero J. 426P Spotlight on refractory metastatic colorectal cancer (refMCRC): Role of prognostic characteristics in the continuum of care. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Capdevila J, Landolfi S, Hernando J, Teule A, Garcia-Carbonero R, Custodio A, Cubillo A, Alonso-Gordoa T, Carmona-Bayonas A, Crespo G, Blanco M, Viudez A, La Casta A, Sevilla I, Segura Á, López C, Benavent Viñuales M, Nuciforo P, Manzano J. 1107P Durvalumab plus tremelimumab in patients with grade 3 neuroendocrine neoplasms of gastroenteropancreatic origin: Updated results from the multicenter phase II DUNE trial (GETNE 1601). Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Hernando J, Manzano J, Teule A, López C, Garcia-Carbonero R, Benavent Viñuales M, Custodio A, Cubillo A, Alonso V, Alonso-Gordoa T, Carmona-Bayonas A, Crespo G, Blanco M, Jimenez-Fonseca P, Viudez A, La Casta A, Sevilla I, Llanos M, Segura Á, Capdevila J. 1099MO Durvalumab plus tremelimumab influence on response to subsequent treatments in patients with neuroendocrine neoplasms (NENs) of gastroenteropancreatic and lung origins: Results from the phase II DUNE trial (GETNE 1601). Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Lo CH, Nguyen LH, Drew DA, Warner ET, Joshi AD, Graham MS, Anyane-Yeboa A, Shebl FM, Astley CM, Figueiredo JC, Guo CG, Ma W, Mehta RS, Kwon S, Song M, Davies R, Capdevila J, Sudre CH, Wolf J, Cozier YC, Rosenberg L, Wilkens LR, Haiman CA, Marchand LL, Palmer JR, Spector TD, Ourselin S, Steves CJ, Chan AT. Race, ethnicity, community-level socioeconomic factors, and risk of COVID-19 in the United States and the United Kingdom. EClinicalMedicine 2021; 38:101029. [PMID: 34308322 PMCID: PMC8285255 DOI: 10.1016/j.eclinm.2021.101029] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/29/2021] [Accepted: 06/29/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND There is limited prior investigation of the combined influence of personal and community-level socioeconomic factors on racial/ethnic disparities in individual risk of coronavirus disease 2019 (COVID-19). METHODS We performed a cross-sectional analysis nested within a prospective cohort of 2,102,364 participants from March 29, 2020 in the United States (US) and March 24, 2020 in the United Kingdom (UK) through December 02, 2020 via the COVID Symptom Study smartphone application. We examined the contribution of community-level deprivation using the Neighborhood Deprivation Index (NDI) and the Index of Multiple Deprivation (IMD) to observe racial/ethnic disparities in COVID-19 incidence. ClinicalTrials.gov registration: NCT04331509. FINDINGS Compared with non-Hispanic White participants, the risk for a positive COVID-19 test was increased in the US for non-Hispanic Black (multivariable-adjusted odds ratio [OR], 1.32; 95% confidence interval [CI], 1.18-1.47) and Hispanic participants (OR, 1.42; 95% CI, 1.33-1.52) and in the UK for Black (OR, 1.17; 95% CI, 1.02-1.34), South Asian (OR, 1.39; 95% CI, 1.30-1.49), and Middle Eastern participants (OR, 1.38; 95% CI, 1.18-1.61). This elevated risk was associated with living in more deprived communities according to the NDI/IMD. After accounting for downstream mediators of COVID-19 risk, community-level deprivation still mediated 16.6% and 7.7% of the excess risk in Black compared to White participants in the US and the UK, respectively. INTERPRETATION Our results illustrate the critical role of social determinants of health in the disproportionate COVID-19 risk experienced by racial and ethnic minorities.
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Affiliation(s)
- Chun-Han Lo
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Long H. Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - David A. Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Erica T. Warner
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Harvard/MGH Center on Genomics, Vulnerable Populations, And Health Disparities, Massachusetts General Hospital, Boston, MA, USA
| | - Amit D. Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mark S. Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Adjoa Anyane-Yeboa
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Fatma M. Shebl
- Medical Practice Evaluation Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christina M. Astley
- Computational Epidemiology Lab and Division of Endocrinology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jane C. Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles California, USA
| | - Chuan-Guo Guo
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Wenjie Ma
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Raaj S. Mehta
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sohee Kwon
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mingyang Song
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | | | - Carole H. Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | | | - Lynn Rosenberg
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Lynne R. Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Julie R. Palmer
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Claire J. Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Ageing and Health, Guy's and St Thomas's NHS Foundation Trust, London, UK
| | - Andrew T. Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Corresponding author at: Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 100 Cambridge Street, 15th Floor, Boston, MA 02114, USA.
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Dijkstra E, Hospers G, van de Velde C, Fleer J, Bahadoer R, Guren M, Tjalma J, Putter H, Meershoek-Klein Kranenbarg E, Roodvoets A, ten Tije A, Capdevila J, Hendriks M, Cervantes A, Nilsson P, Glimelius B, van Etten B, Marijnen C. OC-0337 Quality of life, functional outcome and late toxicity in patients treated within the RAPIDO trial. Radiother Oncol 2021. [DOI: 10.1016/s0167-8140(21)06870-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Menni C, Klaser K, May A, Polidori L, Capdevila J, Louca P, Sudre CH, Nguyen LH, Drew DA, Merino J, Hu C, Selvachandran S, Antonelli M, Murray B, Canas LS, Molteni E, Graham MS, Modat M, Joshi AD, Mangino M, Hammers A, Goodman AL, Chan AT, Wolf J, Steves CJ, Valdes AM, Ourselin S, Spector TD. Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID Symptom Study app in the UK: a prospective observational study. Lancet Infect Dis 2021; 21:939-949. [PMID: 33930320 PMCID: PMC8078878 DOI: 10.1016/s1473-3099(21)00224-3] [Citation(s) in RCA: 576] [Impact Index Per Article: 192.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 03/26/2021] [Accepted: 04/01/2021] [Indexed: 01/13/2023]
Abstract
BACKGROUND The Pfizer-BioNTech (BNT162b2) and the Oxford-AstraZeneca (ChAdOx1 nCoV-19) COVID-19 vaccines have shown excellent safety and efficacy in phase 3 trials. We aimed to investigate the safety and effectiveness of these vaccines in a UK community setting. METHODS In this prospective observational study, we examined the proportion and probability of self-reported systemic and local side-effects within 8 days of vaccination in individuals using the COVID Symptom Study app who received one or two doses of the BNT162b2 vaccine or one dose of the ChAdOx1 nCoV-19 vaccine. We also compared infection rates in a subset of vaccinated individuals subsequently tested for SARS-CoV-2 with PCR or lateral flow tests with infection rates in unvaccinated controls. All analyses were adjusted by age (≤55 years vs >55 years), sex, health-care worker status (binary variable), obesity (BMI <30 kg/m2vs ≥30 kg/m2), and comorbidities (binary variable, with or without comorbidities). FINDINGS Between Dec 8, and March 10, 2021, 627 383 individuals reported being vaccinated with 655 590 doses: 282 103 received one dose of BNT162b2, of whom 28 207 received a second dose, and 345 280 received one dose of ChAdOx1 nCoV-19. Systemic side-effects were reported by 13·5% (38 155 of 282 103) of individuals after the first dose of BNT162b2, by 22·0% (6216 of 28 207) after the second dose of BNT162b2, and by 33·7% (116 473 of 345 280) after the first dose of ChAdOx1 nCoV-19. Local side-effects were reported by 71·9% (150 023 of 208 767) of individuals after the first dose of BNT162b2, by 68·5% (9025 of 13 179) after the second dose of BNT162b2, and by 58·7% (104 282 of 177 655) after the first dose of ChAdOx1 nCoV-19. Systemic side-effects were more common (1·6 times after the first dose of ChAdOx1 nCoV-19 and 2·9 times after the first dose of BNT162b2) among individuals with previous SARS-CoV-2 infection than among those without known past infection. Local effects were similarly higher in individuals previously infected than in those without known past infection (1·4 times after the first dose of ChAdOx1 nCoV-19 and 1·2 times after the first dose of BNT162b2). 3106 of 103 622 vaccinated individuals and 50 340 of 464 356 unvaccinated controls tested positive for SARS-CoV-2 infection. Significant reductions in infection risk were seen starting at 12 days after the first dose, reaching 60% (95% CI 49-68) for ChAdOx1 nCoV-19 and 69% (66-72) for BNT162b2 at 21-44 days and 72% (63-79) for BNT162b2 after 45-59 days. INTERPRETATION Systemic and local side-effects after BNT162b2 and ChAdOx1 nCoV-19 vaccination occur at frequencies lower than reported in phase 3 trials. Both vaccines decrease the risk of SARS-CoV-2 infection after 12 days. FUNDING ZOE Global, National Institute for Health Research, Chronic Disease Research Foundation, National Institutes of Health, UK Medical Research Council, Wellcome Trust, UK Research and Innovation, American Gastroenterological Association.
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Affiliation(s)
- Cristina Menni
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.
| | - Kerstin Klaser
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | | | | | - Panayiotis Louca
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Carole H Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Medical Research Council Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, and Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Long H Nguyen
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - David A Drew
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | | | | | - Michela Antonelli
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Benjamin Murray
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Liane S Canas
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Erika Molteni
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Mark S Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Amit D Joshi
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Massimo Mangino
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK; National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, UK
| | - Alexander Hammers
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Anna L Goodman
- Department of Infection, Guy's and St Thomas' Foundation Trust, St Thomas Hospital, London, UK
| | - Andrew T Chan
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Claire J Steves
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - Ana M Valdes
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK; Nottingham NIHR Biomedical Research Centre at the School of Medicine, University of Nottingham, Nottingham City Hospital, Nottingham, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Tim D Spector
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
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26
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Bowyer RCE, Varsavsky T, Thompson EJ, Sudre CH, Murray BAK, Freidin MB, Yarand D, Ganesh S, Capdevila J, Bakker E, Cardoso MJ, Davies R, Wolf J, Spector TD, Ourselin S, Steves CJ, Menni C. Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app. Thorax 2021; 76:723-725. [PMID: 33376145 PMCID: PMC8223682 DOI: 10.1136/thoraxjnl-2020-215119] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 11/23/2020] [Accepted: 11/24/2020] [Indexed: 11/21/2022]
Abstract
Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 1 960 242 unique users in Great Britain (GB) of the COVID-19 Symptom Study app, we estimated that, concurrent to the GB government sanctioning lockdown, COVID-19 was distributed across GB, with evidence of 'urban hotspots'. We found a geo-social gradient associated with predicted disease prevalence suggesting urban areas and areas of higher deprivation are most affected. Our results demonstrate use of self-reported symptoms data to provide focus on geographical areas with identified risk factors.
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Affiliation(s)
| | - Thomas Varsavsky
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | - Carole H Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Benjamin A K Murray
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | | | | | | | | | - M Jorge Cardoso
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | | | | | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
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Merino J, Berry S, Ganesh S, Capdevila J, Drew D, Bakker E, Wolf J, Franks P, Chan A, Spector T, Ordovas J, Valdes A. Precision Nutrition and Reliability of Continuous Glucose Monitors: Insights From the PREDICT Study. Curr Dev Nutr 2021. [DOI: 10.1093/cdn/nzab041_028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Objectives
The use of continuous glucose monitors (CGM) provides a more in-depth characterization of glycemic variation in response to environmental stimuli, but concerns about CGM reliability for categorizing glycemic responses to foods and meals exist. We sought to evaluate the concordance and reliability of two simultaneously worn CGM devices on postprandial glycemic responses.
Methods
We examined the correlation and coefficient of variation of the 2h glucose incremental area under the curve (iAUC) for 21,527 standardized and ad libitum meals consumed by 368 healthy participants from the PREDICT-1 Study. Included participants were simultaneously monitored with either two Abbott Freestyle Libre Pro devices (n = 339, same device group) or the combination of Abbott Freestyle Libre Pro and Dexcom G6 devices (n = 29, inter device group).
Within-subject 2 h iAUC glucose meal rankings for paired CGM devices were assessed using the Kendal-tau measure for ranking concordance.
Results
The correlation coefficient of the 2 h glucose iAUC for paired CGM devices was 0.97 (95% CI, 0.96 to 0.97) for same device comparisons and 0.78 (0.76 to 0.80) for inter device comparisons. The coefficient of variation of the 2 h glucose iAUC for standardized meals was 5.1% (interquartile range, 2.2 to 10.1) for same device comparisons and 15.1% (5.9 to 31.2) for inter device comparisons. Similar results were observed for ad libitum meals with same and inter device coefficients of variation of 8.9% (3.3 to 21.3) and 24.2% (10.2 to 53.1%), respectively. Meal rankings for the 2 h glucose iAUC were concordant between paired CGM devices, with a mean Kendall rank correlation coefficient of 0.86 (sd = 0.07) for same device comparisons and 0.63 (sd = 0.011) for inter device comparisons.
Conclusions
These data provide evidence for repeatability and concordance for ranking of glycemic responses, and suggest that factors other than CGM sensors mostly drive within-subject meal categorization. Our findings are critical for identifying sources of variability in glycemic responses for the eventual implementation of precision nutrition.
Funding Sources
Zoe Global, UK Government Department of Health and Social Care, Wellcome Trust. National Institutes of Health.
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Graham MS, Sudre CH, May A, Antonelli M, Murray B, Varsavsky T, Kläser K, Canas LS, Molteni E, Modat M, Drew DA, Nguyen LH, Polidori L, Selvachandran S, Hu C, Capdevila J, Hammers A, Chan AT, Wolf J, Spector TD, Steves CJ, Ourselin S. Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study. Lancet Public Health 2021; 6:e335-e345. [PMID: 33857453 PMCID: PMC8041365 DOI: 10.1016/s2468-2667(21)00055-4] [Citation(s) in RCA: 206] [Impact Index Per Article: 68.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 03/05/2021] [Accepted: 03/10/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. METHODS We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. FINDINGS From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6-0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56-0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38-0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02-1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. INTERPRETATION The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. FUNDING Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society.
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Affiliation(s)
- Mark S Graham
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; MRC Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | | | - Michela Antonelli
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Benjamin Murray
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Thomas Varsavsky
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Kerstin Kläser
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Liane S Canas
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Long H Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | | | | | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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29
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Graham MS, Sudre CH, May A, Antonelli M, Murray B, Varsavsky T, Kläser K, Canas LS, Molteni E, Modat M, Drew DA, Nguyen LH, Polidori L, Selvachandran S, Hu C, Capdevila J, Hammers A, Chan AT, Wolf J, Spector TD, Steves CJ, Ourselin S. Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study. Lancet Public Health 2021; 6:e335-e345. [PMID: 33857453 DOI: 10.1101/2021.03.28.21254404] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 03/05/2021] [Accepted: 03/10/2021] [Indexed: 05/27/2023]
Abstract
BACKGROUND The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. METHODS We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. FINDINGS From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6-0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56-0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38-0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02-1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. INTERPRETATION The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. FUNDING Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society.
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Affiliation(s)
- Mark S Graham
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; MRC Unit for Lifelong Health and Ageing, Department of Population Science and Experimental Medicine, University College London, London, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | | | - Michela Antonelli
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Benjamin Murray
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Thomas Varsavsky
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Kerstin Kläser
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Liane S Canas
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Long H Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | | | | | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Antonelli M, Capdevila J, Chaudhari A, Granerod J, Canas LS, Graham MS, Klaser K, Modat M, Molteni E, Murray B, Sudre CH, Davies R, May A, Nguyen LH, Drew DA, Joshi A, Chan AT, Cramer JP, Spector T, Wolf J, Ourselin S, Steves CJ, Loeliger AE. Optimal symptom combinations to aid COVID-19 case identification: Analysis from a community-based, prospective, observational cohort. J Infect 2021; 82:384-390. [PMID: 33592254 PMCID: PMC7881291 DOI: 10.1016/j.jinf.2021.02.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 02/08/2021] [Accepted: 02/10/2021] [Indexed: 01/10/2023]
Abstract
Objectives Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. Methods UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. Findings UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. Interpretation We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.
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Affiliation(s)
- M Antonelli
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | | | - A Chaudhari
- Coalition for Epidemic Preparedness Innovations, London, United Kingdom
| | - J Granerod
- Coalition for Epidemic Preparedness Innovations, London, United Kingdom
| | - L S Canas
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - M S Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - K Klaser
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - M Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - E Molteni
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - B Murray
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - C H Sudre
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom; MRC Unit for Lifelong Health and Ageing at UCL/Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom
| | - R Davies
- Zoe Global, London, United Kingdom
| | - A May
- Zoe Global, London, United Kingdom
| | - L H Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - D A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - A Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - A T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - J P Cramer
- Coalition for Epidemic Preparedness Innovations, London, United Kingdom
| | - T Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - J Wolf
- Zoe Global, London, United Kingdom
| | - S Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - C J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.
| | - A E Loeliger
- Coalition for Epidemic Preparedness Innovations, London, United Kingdom
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31
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Antonelli M, Capdevila J, Chaudhari A, Granerod J, Canas LS, Graham MS, Klaser K, Modat M, Molteni E, Murray B, Sudre CH, Davies R, May A, Nguyen LH, Drew DA, Joshi A, Chan AT, Cramer JP, Spector T, Wolf J, Ourselin S, Steves CJ, Loeliger AE. Optimal symptom combinations to aid COVID-19 case identification: analysis from a community-based, prospective, observational cohort. medRxiv 2021:2020.11.23.20237313. [PMID: 33269364 PMCID: PMC7709185 DOI: 10.1101/2020.11.23.20237313] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
OBJECTIVES Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health. METHODS UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity. FINDINGS UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC. INTERPRETATION We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.
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Affiliation(s)
- M Antonelli
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | - A Chaudhari
- Coalition for Epidemic Preparedness Innovations, London, UK
| | - J Granerod
- Coalition for Epidemic Preparedness Innovations, London, UK
| | - L S Canas
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - M S Graham
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - K Klaser
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - M Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - E Molteni
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - B Murray
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - C H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL/Centre for Medical Image Computing, Department of Computer Science, UCL, London, UK
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | | | - L H Nguyen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - D A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - A Joshi
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - A T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - J P Cramer
- Coalition for Epidemic Preparedness Innovations, London, UK
| | - T Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - S Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - C J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - A E Loeliger
- Coalition for Epidemic Preparedness Innovations, London, UK
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Berry SE, Valdes AM, Drew DA, Asnicar F, Mazidi M, Wolf J, Capdevila J, Hadjigeorgiou G, Davies R, Khatib HA, Bonnett C, Ganesh S, Bakker E, Hart D, Mangino M, Merino J, Linenberg I, Wyatt P, Ordovas JM, Gardner CD, Delahanty LM, Chan AT, Segata N, Franks PW, Spector TD. Publisher Correction: Human postprandial responses to food and potential for precision nutrition. Nat Med 2020; 26:1802. [PMID: 33082577 DOI: 10.1038/s41591-020-1130-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Affiliation(s)
- Sarah E Berry
- Department of Nutrition, King's College London, London, UK
| | - Ana M Valdes
- School of Medicine, University of Nottingham, Nottingham, UK. .,Nottingham NIHR Biomedical Research Centre, Nottingham, UK.
| | - David A Drew
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Mohsen Mazidi
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
| | | | | | | | | | - Haya Al Khatib
- Department of Nutrition, King's College London, London, UK.,Zoe Global Ltd, London, UK
| | | | | | | | - Deborah Hart
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
| | - Massimo Mangino
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
| | - Jordi Merino
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain
| | | | | | - Jose M Ordovas
- JM-USDA-HNRCA at Tufts University, Boston, MA, USA.,IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
| | | | - Linda M Delahanty
- Diabetes Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy
| | - Paul W Franks
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK.,Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tim D Spector
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK.
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Serna G, Ruiz-Pace F, Hernando J, Alonso L, Fasani R, Landolfi S, Comas R, Jimenez J, Elez E, Bullman S, Tabernero J, Capdevila J, Dienstmann R, Nuciforo P. Fusobacterium nucleatum persistence and risk of recurrence after preoperative treatment in locally advanced rectal cancer. Ann Oncol 2020; 31:1366-1375. [PMID: 32569727 PMCID: PMC7542577 DOI: 10.1016/j.annonc.2020.06.003] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 06/04/2020] [Accepted: 06/05/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Accumulating evidence has identified Fusobacterium as an important pathogenic gut bacterium associated with colorectal cancer. Nevertheless, only limited data exist about the role of this bacterium in locally advanced rectal cancer (LARC). In this study, we quantified Fusobacterium nucleatum in untreated and post-neoadjuvant chemoradiotherapy (nCRT) samples from LARC patients and investigated its association with therapy response and survival. PATIENTS AND METHODS A total of 254 samples from 143 patients with rectal adenocarcinomas were analyzed for the presence and abundance of F. nucleatum using RNA in situ hybridization and digital image analysis. Assay accuracy was determined using infected cell lines and tumor samples with available quantitative PCR data. We studied the impact of F. nucleatum load on pathologic complete response and relapse-free survival. Treatment-induced changes were evaluated in paired pre- and post-nCRT samples (n = 71). Finally, tumor microenvironment changes during nCRT were assessed in paired samples (n = 45) by immune contexture analysis. RESULTS F. nucleatum tissue levels by RNA in situ hybridization strongly correlated with quantitative PCR (r = 0.804, P < 0.001). F. nucleatum abundance was higher in untreated [median, 7.4; 95% confidence interval (3.7-16.2)] compared with treated [median, 1.6; 95% confidence interval (1.3-2.4)] tumors (P <0.001) with 58% (73/126) and 26% (22/85) positive tumors, respectively (P < 0.001). Baseline F. nucleatum levels were not associated with pathologic complete response. F. nucleatum positivity after nCRT, but not baseline status, significantly increased risk of relapse [hazard ratio = 7.5, 95% confidence interval (3.0-19.0); P < 0.001]. Tumors that turned F. nucleatum-negative after nCRT had a strong increase in CD8+ T cells post-nCRT (P < 0.001), while those that persisted F. nucleatum-positive after nCRT lacked CD8+ T cells induction in post-nCRT samples compared with baseline (P = 0.69). CONCLUSION F. nucleatum persistence post-nCRT is associated with high relapse rates in LARC, potentially linked to suppression of immune cytotoxicity.
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Affiliation(s)
- G Serna
- Molecular Oncology Group, Spain
| | - F Ruiz-Pace
- Oncology Data Science Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - J Hernando
- Medical Oncology Department, Gastrointestinal and Endocrine Tumor Unit, Vall d'Hebron University Hospital, Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | | | | | - S Landolfi
- Department of Pathology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - R Comas
- Oncology Data Science Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | | | - E Elez
- Medical Oncology Department, Gastrointestinal and Endocrine Tumor Unit, Vall d'Hebron University Hospital, Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - S Bullman
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, USA
| | - J Tabernero
- Medical Oncology Department, Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology (VHIO), IOB-Quiron, UVic-UCC, Barcelona, Spain
| | - J Capdevila
- Medical Oncology Department, Gastrointestinal and Endocrine Tumor Unit, Vall d'Hebron University Hospital, Vall Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - R Dienstmann
- Oncology Data Science Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
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Hernando J, Zafon C, Diez-Villanueva A, Iglesias C, Rodriguez H, Villalmazo N, Gil J, Klein-Hesselink E, Roca M, Verdaguer H, Acosta Eyzaguirre D, Diez Garcia M, Lindo E, Hernandez-Losa J, Reverter J, Puig-Domingo M, Links T, Capdevila J, Jordà M. 1925P DNA methylation signature for prediction of metastasis and response to multikinase inhibitors of differentiated thyroid carcinoma (DTC). Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Fonseca PJ, La Salvia A, Capdevila J, Castaño A, Benavent M, Alonso-Orduna V, Alonso T, Canovas MS, Custodio A, Centeno RG, Llanos M, Crespo G, Lopez de Sa A, Teule A, Fernández LO, Torres I, Plazas JG, Pericay C, Villabona C, López C. 1159MO Survival and prognostic factors analysis of 535 grade 3 gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN): Data from the Spanish Taskforce of Neuroendocrine Tumours Registry (R-GETNE). Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Rao S, Capdevila J, Gilbert D, Kim S, Dahan L, Kayyal T, Fakih M, Demols A, Jensen L, Spindler KL, Arnold D, Tamberi S, Guren M, Cornfeld M, Jones M, Tian C, Catlett M, Spano JP. LBA42 POD1UM-202: Phase II study of retifanlimab in patients (pts) with squamous carcinoma of the anal canal (SCAC) who progressed following platinum-based chemotherapy. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.2272] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Capdevila J, Teule A, López C, García-Carbonero R, Benavent M, Custodio A, Cubillo A, Alonso V, Gordoa TA, Carmona-Bayonas A, Crespo G, Blanco-Codesido M, Jimenez-Fonseca P, Viúdez A, La Casta Muñoa A, Sevilla I, Llanos M, Segura A, Hernando-Cubero J, Manzano J. 1157O A multi-cohort phase II study of durvalumab plus tremelimumab for the treatment of patients (pts) with advanced neuroendocrine neoplasms (NENs) of gastroenteropancreatic or lung origin: The DUNE trial (GETNE 1601). Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1370] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
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Santa Gadea OS, Hernando-Calvo A, Berché R, Matos I, Gardeazabal I, Pedrazzoli AA, Villar MV, Braña I, Casal GA, Galvao de Aguiar V, Pedrola A, Martinez GA, Mercadé TM, Capdevila J, Cedres S, Oaknin A, Elez E, Tabernero J, Dienstmann R, Garralda E. 572P Limited efficacy of immunotherapy combination regimens in patients with unselected “cold” tumours enrolled in early clinical trials. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Hernando J, Tarasova V, Hu M, Sherman E, Brose M, Robinson B, Tahara M, Wirth L, Sashegyi A, Soldatenkova V, Lin B, Wright J, Hoff A, Leboulleux S, Elisei R, Capdevila J. 1927TiP LIBRETTO-531: Selpercatinib in patients with treatment (Tx)-naïve RET-mutant medullary thyroid cancer (MTC). Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.08.1415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo CG, Ma W, Mehta RS, Warner ET, Sikavi DR, Lo CH, Kwon S, Song M, Mucci LA, Stampfer MJ, Willett WC, Eliassen AH, Hart JE, Chavarro JE, Rich-Edwards JW, Davies R, Capdevila J, Lee KA, Lochlainn MN, Varsavsky T, Sudre CH, Cardoso MJ, Wolf J, Spector TD, Ourselin S, Steves CJ, Chan AT. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Health 2020; 5:e475-e483. [PMID: 32745512 PMCID: PMC7491202 DOI: 10.1016/s2468-2667(20)30164-x] [Citation(s) in RCA: 1267] [Impact Index Per Article: 316.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/13/2020] [Accepted: 07/13/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk. METHODS We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Symptom Study smartphone application (app) from March 24 (UK) and March 29 (USA) to April 23, 2020. Participants were voluntary users of the app and at first use provided information on demographic factors (including age, sex, race or ethnic background, height and weight, and occupation) and medical history, and subsequently reported any COVID-19 symptoms. We used Cox proportional hazards modelling to estimate multivariate-adjusted hazard ratios (HRs) of our primary outcome, which was a positive COVID-19 test. The COVID Symptom Study app is registered with ClinicalTrials.gov, NCT04331509. FINDINGS Among 2 035 395 community individuals and 99 795 front-line health-care workers, we recorded 5545 incident reports of a positive COVID-19 test over 34 435 272 person-days. Compared with the general community, front-line health-care workers were at increased risk for reporting a positive COVID-19 test (adjusted HR 11·61, 95% CI 10·93-12·33). To account for differences in testing frequency between front-line health-care workers and the general community and possible selection bias, an inverse probability-weighted model was used to adjust for the likelihood of receiving a COVID-19 test (adjusted HR 3·40, 95% CI 3·37-3·43). Secondary and post-hoc analyses suggested adequacy of PPE, clinical setting, and ethnic background were also important factors. INTERPRETATION In the UK and the USA, risk of reporting a positive test for COVID-19 was increased among front-line health-care workers. Health-care systems should ensure adequate availability of PPE and develop additional strategies to protect health-care workers from COVID-19, particularly those from Black, Asian, and minority ethnic backgrounds. Additional follow-up of these observational findings is needed. FUNDING Zoe Global, Wellcome Trust, Engineering and Physical Sciences Research Council, National Institutes of Health Research, UK Research and Innovation, Alzheimer's Society, National Institutes of Health, National Institute for Occupational Safety and Health, and Massachusetts Consortium on Pathogen Readiness.
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Affiliation(s)
- Long H Nguyen
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - David A Drew
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mark S Graham
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Amit D Joshi
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Chuan-Guo Guo
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Wenjie Ma
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Raaj S Mehta
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Erica T Warner
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center on Genomics, Vulnerable Populations, and Health Disparities, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daniel R Sikavi
- Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Chun-Han Lo
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Sohee Kwon
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mingyang Song
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Meir J Stampfer
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Walter C Willett
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - A Heather Eliassen
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jaime E Hart
- Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jorge E Chavarro
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T H Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Janet W Rich-Edwards
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | - Karla A Lee
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Mary Ni Lochlainn
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Thomas Varsavsky
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | | | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Andrew T Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Immunology and Infectious Disease, Harvard T H Chan School of Public Health, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA; Massachusetts Consortium on Pathogen Readiness, Cambridge, MA, USA.
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Berry SE, Valdes AM, Drew DA, Asnicar F, Mazidi M, Wolf J, Capdevila J, Hadjigeorgiou G, Davies R, Al Khatib H, Bonnett C, Ganesh S, Bakker E, Hart D, Mangino M, Merino J, Linenberg I, Wyatt P, Ordovas JM, Gardner CD, Delahanty LM, Chan AT, Segata N, Franks PW, Spector TD. Human postprandial responses to food and potential for precision nutrition. Nat Med 2020; 26:964-973. [PMID: 32528151 PMCID: PMC8265154 DOI: 10.1038/s41591-020-0934-0] [Citation(s) in RCA: 325] [Impact Index Per Article: 81.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 05/11/2020] [Indexed: 12/18/2022]
Abstract
Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. We recruited n = 1,002 twins and unrelated healthy adults in the United Kingdom to the PREDICT 1 study and assessed postprandial metabolic responses in a clinical setting and at home. We observed large inter-individual variability (as measured by the population coefficient of variation (s.d./mean, %)) in postprandial responses of blood triglyceride (103%), glucose (68%) and insulin (59%) following identical meals. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6.0% and 15.4%, respectively); genetic variants had a modest impact on predictions (9.5% for glucose, 0.8% for triglyceride, 0.2% for C-peptide). Findings were independently validated in a US cohort (n = 100 people). We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. These findings may be informative for developing personalized diet strategies. The ClinicalTrials.gov registration identifier is NCT03479866.
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Affiliation(s)
- Sarah E Berry
- Department of Nutrition, King's College London, London, UK
| | - Ana M Valdes
- School of Medicine, University of Nottingham, Nottingham, UK.
- Nottingham NIHR Biomedical Research Centre, Nottingham, UK.
| | - David A Drew
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Mohsen Mazidi
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
| | | | | | | | | | - Haya Al Khatib
- Department of Nutrition, King's College London, London, UK
- Zoe Global Ltd, London, UK
| | | | | | | | - Deborah Hart
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
| | - Massimo Mangino
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
| | - Jordi Merino
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain
| | | | | | - Jose M Ordovas
- JM-USDA-HNRCA at Tufts University, Boston, MA, USA
- IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
| | | | - Linda M Delahanty
- Diabetes Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy
| | - Paul W Franks
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tim D Spector
- Department of Twins Research & Genetic Epidemiology, King's College London, London, UK.
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Nguyen LH, Drew DA, Joshi AD, Guo CG, Ma W, Mehta RS, Sikavi DR, Lo CH, Kwon S, Song M, Mucci LA, Stampfer MJ, Willett WC, Eliassen AH, Hart JE, Chavarro JE, Rich-Edwards JW, Davies R, Capdevila J, Lee KA, Lochlainn MN, Varsavsky T, Graham MS, Sudre CH, Cardoso MJ, Wolf J, Ourselin S, Steves CJ, Spector TD, Chan AT. Risk of COVID-19 among frontline healthcare workers and the general community: a prospective cohort study. medRxiv 2020:2020.04.29.20084111. [PMID: 32511531 PMCID: PMC7273299 DOI: 10.1101/2020.04.29.20084111] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background Data for frontline healthcare workers (HCWs) and risk of SARS-CoV-2 infection are limited and whether personal protective equipment (PPE) mitigates this risk is unknown. We evaluated risk for COVID-19 among frontline HCWs compared to the general community and the influence of PPE. Methods We performed a prospective cohort study of the general community, including frontline HCWs, who reported information through the COVID Symptom Study smartphone application beginning on March 24 (United Kingdom, U.K.) and March 29 (United States, U.S.) through April 23, 2020. We used Cox proportional hazards modeling to estimate multivariate-adjusted hazard ratios (aHRs) of a positive COVID-19 test. Findings Among 2,035,395 community individuals and 99,795 frontline HCWs, we documented 5,545 incident reports of a positive COVID-19 test over 34,435,272 person-days. Compared with the general community, frontline HCWs had an aHR of 11·6 (95% CI: 10·9 to 12·3) for reporting a positive test. The corresponding aHR was 3·40 (95% CI: 3·37 to 3·43) using an inverse probability weighted Cox model adjusting for the likelihood of receiving a test. A symptom-based classifier of predicted COVID-19 yielded similar risk estimates. Compared with HCWs reporting adequate PPE, the aHRs for reporting a positive test were 1·46 (95% CI: 1·21 to 1·76) for those reporting PPE reuse and 1·31 (95% CI: 1·10 to 1·56) for reporting inadequate PPE. Compared with HCWs reporting adequate PPE who did not care for COVID-19 patients, HCWs caring for patients with documented COVID-19 had aHRs for a positive test of 4·83 (95% CI: 3·99 to 5·85) if they had adequate PPE, 5·06 (95% CI: 3·90 to 6·57) for reused PPE, and 5·91 (95% CI: 4·53 to 7·71) for inadequate PPE. Interpretation Frontline HCWs had a significantly increased risk of COVID-19 infection, highest among HCWs who reused PPE or had inadequate access to PPE. However, adequate supplies of PPE did not completely mitigate high-risk exposures. Funding Zoe Global Ltd., Wellcome Trust, EPSRC, NIHR, UK Research and Innovation, Alzheimer's Society, NIH, NIOSH, Massachusetts Consortium on Pathogen Readiness.
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Affiliation(s)
- Long H. Nguyen
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - David A. Drew
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
| | - Amit D. Joshi
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
| | - Chuan-Guo Guo
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - Wenjie Ma
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Raaj S. Mehta
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel R. Sikavi
- Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Chun-Han Lo
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sohee Kwon
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
| | - Mingyang Song
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Lorelei A. Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Meir J. Stampfer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Walter C. Willett
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - A. Heather Eliassen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jaime E. Hart
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jorge E. Chavarro
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Janet W. Rich-Edwards
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School. Boston, MA, U.S.A
| | | | | | - Karla A. Lee
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, U.K
| | - Mary Ni Lochlainn
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, U.K
| | - Thomas Varsavsky
- School of Biomedical Engineering & Imaging Sciences, King’s College London. London, U.K
| | - Mark S. Graham
- School of Biomedical Engineering & Imaging Sciences, King’s College London. London, U.K
| | - Carole H. Sudre
- School of Biomedical Engineering & Imaging Sciences, King’s College London. London, U.K
| | - M. Jorge Cardoso
- School of Biomedical Engineering & Imaging Sciences, King’s College London. London, U.K
| | | | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King’s College London. London, U.K
| | - Claire J. Steves
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, U.K
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, U.K
| | - Andrew T. Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, MA, USA
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health. Boston, MA, USA
- Broad Institute of MIT and Harvard. Cambridge, MA, USA
- Massachusetts Consortium on Pathogen Readiness, Cambridge, MA, USA
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Hollebecque A, de Bono J, Salvagni S, Plummer R, Niccoli P, Capdevila J, Curigliano G, Moreno V, De Braud F, López-Brea M, Martin-Romano P, Baudin E, Arias M, De Alvaro J, Parra-Palau J, Sánchez-Pérez T, Aronchik I, Filvaroff E, Lamba M, Nikolova Z. 18O CC-90011 in patients (Pts) with advanced solid tumors (STs) and relapsed/refractory non-Hodgkin lymphoma (R/R NHL): Updated results of a phase I study. Ann Oncol 2020. [DOI: 10.1016/j.annonc.2020.01.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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44
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Capdevila J, Mayor R, Mancuso FM, Iglesias C, Caratù G, Matos I, Zafón C, Hernando J, Petit A, Nuciforo P, Cameselle-Teijeiro JM, Álvarez C, Recio JA, Tabernero J, Matias-Guiu X, Vivancos A, Seoane J. Early evolutionary divergence between papillary and anaplastic thyroid cancers. Ann Oncol 2019; 29:1454-1460. [PMID: 29648575 DOI: 10.1093/annonc/mdy123] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Background Papillary thyroid cancer (PTC) is the most common thyroid carcinoma and exhibits an almost uniformly good prognosis, while anaplastic thyroid cancer (ATC) is less frequent and is one of the most aggressive cancers usually resistant to conventional treatment. Current hypothesis posits that ATC derives from PTC through the progressive acquisition of a discrete number of genomic alterations and implies that the mutational landscape of ATC resembles that of PTC. However, the clinical behaviour of ATC and PTC is radically different. We decided to address the disconnection between the clinical behaviour of ATC and PTC and the proposed model of the progressive development of ATC from PTC. Patients and methods We carried out exome sequencing of DNA from 14 ATC specimens including three cases of concomitant ATC and PTC as well as their corresponding normal DNA from 14 patients. The sequencing results were validated using droplet digital PCR. We carried out immunohistochemistry and immunofluorescence studies of the concomitant ATC and PTC cases. In addition, we integrated our sequencing results with the existing TCGA data. Results Most of the somatic mutations identified in the ATC component differed from the ones in PTC in the cases of concomitant ATC and PTC. The trunks of the phylogenetic trees representing the somatic mutations were short with long branches. In one case of concomitant PTC and ATC specimens, we observed an infiltration of PTC cells within the ATC component. Moreover, we integrated our results with data obtained from TCGA and observed that the most frequent mutations found in ATC presented high cancer cell fraction values and were significantly different from the PTC ones. Conclusion ATC diverge from PTC early in tumour development and both tumour types evolve independently. Our work allows the understanding of the relationship between ATC and PTC facilitating the clinical management of these malignancies.
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Affiliation(s)
- J Capdevila
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - R Mayor
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - F M Mancuso
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - C Iglesias
- Vall d Hebron Institute of Research (VHIR), Vall d'Hebron University Hospital, Barcelona
| | - G Caratù
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - I Matos
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - C Zafón
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - J Hernando
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - A Petit
- IDIBELL, Department of Pathology, Hospital Universitari de Bellvitge Universidad de Barcelona, Barcelona
| | - P Nuciforo
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona
| | - J M Cameselle-Teijeiro
- Clinical University Hospital, University of Santiago de Compostela, Santiago de Compostela
| | - C Álvarez
- Clinical University Hospital, University of Santiago de Compostela, Santiago de Compostela
| | - J A Recio
- Vall d Hebron Institute of Research (VHIR), Vall d'Hebron University Hospital, Barcelona
| | - J Tabernero
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona; CIBERONC, Barcelona; Universitat Autònoma de Barcelona, Cerdanyola del Vallès
| | - X Matias-Guiu
- IDIBELL, Department of Pathology, Hospital Universitari de Bellvitge Universidad de Barcelona, Barcelona; CIBERONC, Barcelona; Department of Pathology, Hospital Universitari Arnau de Vilanova de Lleida University of Lleida, IRBLleida, Lleida
| | - A Vivancos
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona.
| | - J Seoane
- Vall d'Hebron Institute of Oncology (VHIO) Vall d'Hebron University Hospital, Barcelona; CIBERONC, Barcelona; Universitat Autònoma de Barcelona, Cerdanyola del Vallès; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
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Kulke MH, Ruszniewski P, Van Cutsem E, Lombard-Bohas C, Valle JW, De Herder WW, Pavel M, Degtyarev E, Brase JC, Bubuteishvili-Pacaud L, Voi M, Salazar R, Borbath I, Fazio N, Smith D, Capdevila J, Riechelmann RP, Yao JC. A randomized, open-label, phase 2 study of everolimus in combination with pasireotide LAR or everolimus alone in advanced, well-differentiated, progressive pancreatic neuroendocrine tumors: COOPERATE-2 trial. Ann Oncol 2019; 30:1846. [PMID: 31407000 PMCID: PMC8902961 DOI: 10.1093/annonc/mdz219] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023] Open
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Capdevila J, Mayor R, Mancuso FM, Iglesias C, Caratú G, Matos I, Zafón C, Hernando J, Petit A, Nuciforo P, Cameselle-Teijeiro JM, Álvarez CV, Recio JA, Tabernero J, Matias-Guiu X, Vivancos A, Seoane J. Early evolutionary divergence between papillary and anaplastic thyroid cancers. Ann Oncol 2019; 30:1843. [PMID: 31406995 DOI: 10.1093/annonc/mdz216] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Hollebecque A, de Bono J, Salvagni S, Plummer R, Isambert N, Niccoli P, Capdevila J, Curigliano G, Moreno V, De Braud F, López-Brea M, Martin-Romano P, Baudin E, Arias M, de Alvaro J, Parra-Palau J, Sánchez Pérez T, Filvaroff E, Lamba M, Nikolova Z. Phase I study of CC-90011 in patients with advanced solid tumours (STs) and relapsed/refractory non-hodgkin lymphoma (R/R NHL). Ann Oncol 2019. [DOI: 10.1093/annonc/mdz256.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Hernando Cubero J, García Álvarez A, Roca Herrera M, Acosta D, Diez M, Ferrer R, Garcia Burillo A, Zafon C, Iglesias C, Capdevila J. Correlation of thyroglobulin (Tg) oscillations with progression-free survival (PFS) in patients with radioactive iodine-refractory (RAI-R) differentiated thyroid carcinoma (DTC) treated with multikinase inhibitors (MKI). Ann Oncol 2019. [DOI: 10.1093/annonc/mdz267.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Hernando Cubero J, Grande E, Castellano Gauna D, Ibrahim T, Fazio N, Lopez C, Teulé A, Valle J, Alonso V, Molina-Cerrillo J, Tafuto S, Custodio A, Trejo L, Casteras A, Manneh Kopp R, Miqueo C, Roca Herrera M, Garcia-Carbonero R, Salazar R, Capdevila J. Differences in multikinase inhibitors (MKI) toxicity profile according to gender. A pooled analysis of three phase II trials with lenvatinib, pazopanib and sorafenib in patients (pts) with advanced gastroenteropancreatic (GEP) neuroendocrine tumours (NETs). Ann Oncol 2019. [DOI: 10.1093/annonc/mdz256.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Capdevila J, Castaño J, Mancuso F, Pedraza-Arevalo S, Matos I, Palmer H, Salva F, Landolfi S, Jimenez-Fonseca P, Garcia-Carbonero R, Lopez C, Ogbah Z, Nuciforo P, Casteras A, Acosta D, Diez M, Hernando J, Luque R, Vivancos A. RNA expression profiles and splicing alterations in grade 1/2 neuroendocrine neoplasms from small intestine origin (siNENs). Final results of the GETNE-NETSEQ study. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz256.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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