ABSTRACT
Background: The Omicron (B.1.1.529) SARS-CoV-2 variant is highly transmissible and escapes vaccinal immunity. Evidence is lacking as to the impact of Omicron in oncological patients. Method(s): Capitalizing on OnCovid study data (NCT04393974), we analysed COVID-19 morbidity and case fatality rate at 28 days (CFR28) of unvaccinated patients across 3 phases defined following the evolution of the pandemic in Europe, according to date of COVID-19 diagnosis: "Pre-vaccination" phase (27/02/2020-30/11/2020), "Alpha- Delta variant" phase (01/12/2020-14/12/2021), "Omicron variant" phase (15/12/2021-31/01/2022). Finding(s): By the data lock of 04/02/2022, 3820 patients from 37 institutions across 6 countries were entered. Out of 3473 eligible patients, 2033 (58.6%), 1075 (30.9%) and 365 (10.5%) were diagnosed during the Pre-vaccination, Alpha-Delta and Omicron phases. In total 659 (61.3%) and 42 (11.5%) were unvaccinated in the Alpha-Delta and Omicron. Unvaccinated patients across the Omicron, Alpha-Delta and Pre-vaccination phases experienced similar CFR28 (27.5%, 28%, 29%, respectively). Following propensity score matching, 42 unvaccinated Omicron patients were matched with 122 and 121 patients from the Pre-vaccination and Alpha-Delta phases respectively, based on country of origin, sex, age, comorbidity burden, primary tumour, cancer stage and status, and the receipt of systemic anticancer therapy at COVID-19. Unvaccinated Omicron patients experienced improved COVID-19 outcomes in comparison to patients diagnosed during the Prevaccination phase. Morbidity and mortality were comparable to those of unvaccinated patients diagnosed during the Alpha-Delta phase. Interpretation(s): Despite time-dependent improvements in outcomes reported in the Omicron phase, patients with cancer remain highly vulnerable to SARS-CoV-2 in absence of vaccinal protection. This study provides unequivocal evidence in support of universal vaccination of patients with cancer as a protective measure against morbidity and mortality from COVID-19.
ABSTRACT
We sought to determine parameters of the acute phase response, a feature of innate immunity activated by infectious noxae and cancer, deranged by Covid-19 and establish oncological indices' prognostic potential for patients with concomitant cancer and Covid-19. Between 27/02 and 23/06/2020, OnCovid retrospectively accrued 1,318 consecutive referrals of patients with cancer and Covid-19 aged 18 from the U.K., Spain, Italy, Belgium, and Germany. Patients with myeloma, leukemia, or insufficient data were excluded. The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and prognostic index (PI) were evaluated for their prognostic potential, with the NLR, PLR, and PNI risk stratifications dichotomized around median values and the pre-established risk categorizations from literature utilized for the mGPS and PI. 1,071 eligible patients were randomly assorted into a training set (TS, n=529) and validation set (VS, n=542) matched for age (67.9±13.3 TS, 68.5±13.5 VS), presence of 1 comorbidity (52.1% TS, 49.8% VS), development of 1 Covid-19 complication (27% TS, 25.9% VS), and active malignancy at Covid-19 diagnosis (66.7% TS, 61.6% VS). Among all 1,071 patients, deceased patients tended to categorize into poor risk groups for the NLR, PNI, mGPS, and PI (P<0.0001) with a return to pre-Covid-19 diagnosis NLR, PNI, and mGPS categorizations following recovery (P<0.01). In the TS, higher mortality rates were associated with NLR>6 (44.6% vs 28%, P<0.0001), PNI<40 (46.6% vs 20.9%, P<0.0001), mGPS (50.6% for mGPS2 vs 30.4% and 11.4% for mGPS1 and 0, P<0.0001), and PI (50% for PI2 vs 40% for PI1 and 9.1% for PI0, P<0.0001). Findings were confirmed in the VS (P<0.001 for all comparisons). Patients in poor risk categories had shorter median overall survival [OS], (NLR>6 30 days 95%CI 1-63, PNI<40 23 days 95%CI 10-35, mGPS2 20 days 95%CI 8-32, PI2 23 days 95%CI 1-56) compared to patients in good risk categories, for whom median OS was not reached (P<0.001 for all comparisons). The PLR was not associated with survival. Analyses of survival in the VS confirmed the NLR (P<0.0001), PNI (P<0.0001), PI (P<0.01), and mGPS (P<0.001) as predictors of survival. In a multivariable Cox regression model including all inflammatory indices and pre-established prognostic factors for severe Covid-19 including sex, age, comorbid burden, malignancy status, and receipt of anti-cancer therapy at Covid-19 diagnosis, the PNI was the only factor to emerge with a significant hazard ratio [HR] in both TS and VS analysis (TS HR 1.97, 95%CI 1.19-3.26, P=0.008;VS HR 2.48, 95%CI 1.47- 4.20, P=0.001). We conclude that systemic inflammation drives mortality from Covid-19 through hypoalbuminemia and lymphocytopenia as measured by the PNI and propose the PNI as the OnCovid Inflammatory Score (OIS) in this context.
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Background: There is uncertainty as to the contribution of cancer patients' features on severity and mortality from Covid-19 and little guidance as to the role of anti-cancer and anti-Covid-19 therapy in this population. Method(s): OnCovid is a retrospective observational study conducted across 19 European centers that recruited cancer patients aged >18 and diagnosed with Covid-19 between 26/02 and 01/04/2020. Uni- and multivariable regression models were used to evaluate predictors of Covid-19 severity and mortality. Result(s): We identified 890 patients from UK (n=218, 24%), Italy (n=343, 37%), Spain (n=323, 36%) and Germany (n=6, 1%). Most patients were male (n=503, 56%) had a diagnosis of solid malignancy (n=753, 84%) and 556 (62%) had active disease. Mean (+/-SD) patient age was 68+/-13 years, and 670 (75%) had >1 co-morbidity, most commonly hypertension (n=386, 43%). Commonest presenting symptoms were fever (n=569, 63%) and cough (n=448, 50%), beginning 6.3 (+/-9.5 SD) days before diagnosis. Most patients (n=565, 63%) had >1 complication from Covid-19, including respiratory failure (n=527, 59%) and acute respiratory distress syndrome (n=127, 22%). In total, 110 patients (14%) were escalated to high-dependency or intensive care. At time of analysis, 299 patients had died (33%). Multi-variate logistic regression identified male gender, age>65 (p<0.0001) presence of >2 comorbidities (p=0.001) active malignancy (p=0.07) as predictors of complicated Covid-19. Mortality was associated with active malignancy (p<0.0001), age>65 and co-morbid burden (p=0.002). Provision of chemotherapy, targeted therapy or immunotherapy was not associated with higher mortality. Exposure to anti-malarials alone (chloroquine/hydroxychloroquine, n=182, p<0.001) or in combination with anti-virals (n=195, p<0.001) or tocilizumab (n=51, p=0.004) was associated with improved mortality compared to patients who did not receive any of these therapies (n=446) independent of patients' gender, age, tumour stage and severity of Covid-19. Conclusion(s): This study highlights the clinical utility of demographic factors for individualized risk-stratification of patients and supports further research into emerging anti Covid-19 therapeutics in SARS-Cov-2 infected cancer patients. Clinical trial identification: NCT04393974. Legal entity responsible for the study: Imperial College London. Funding(s): Has not received any funding. Disclosure: D.J. Pinato: Speaker Bureau/Expert testimony: ViiV Healthcare;Advisory/Consultancy, Travel/Accommodation/Expenses: Bayer;Advisory/Consultancy, Speaker Bureau/Expert testimony, Research grant/Funding (institution), Travel/Accommodation/Expenses: BMS;Honoraria (self), Advisory/Consultancy: MiNa Therapeutics;Advisory/Consultancy: Eisai;Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche;Advisory/Consultancy: AstraZeneca;Research grant/Funding (institution): MSD. All other authors have declared no conflicts of interest.Copyright © 2020 European Society for Medical Oncology
ABSTRACT
Background: Despite high contagiousness and rapid spread, SARS-Cov-2 has led to heterogeneous outcomes across affected nations. Within Europe, the United Kingdom is the most severely affected country, with a death toll in excess of 100.000 as of February 2021. We aimed to compare the national impact of Covid19 on the risk of death in UK cancer patients versus those in continental Europe (EU). Methods: We performed a retrospective analysis of the OnCovid study database, a European registry of cancer patients consecutively diagnosed with Covid-19 in 27 centres from February 27 to September 10, 2020. We analysed case fatality rates and risk of death at 30 days and 6 months stratified by region of origin (UK versus EU). We compared patient characteristics at baseline, oncological and Covid-19 specific therapy across cohorts and tested these in multivariable Cox regression models to identify predictors of adverse outcome in UK versus EU patients. Results: Compared to EU patients (n = 924), UK patients (n = 468) were characterised by higher case fatality rates (40.38% versus 26.5%, p < 0.0001), higher risk of death at 30 days (hazard ratio, HR 1.64 [95%CI 1.36-1.99]) and 6 months after Covid-19 diagnosis (47.64% versus 33.33%, p < 0.0001, HR 1.59 [95%CI 1.33-1.88]). UK patients were more often males, of older age and more co-morbid than EU counterparts (p < 0.01). Receipt of anti-cancer therapy was lower in UK versus EU patients (p < 0.001). Despite equal proportions of complicated Covid-19, rates of intensive care admission and use of mechanical ventilation, UK cancer patients were less likely to receive anti-Covid-19 therapies including corticosteroids, anti-virals and interleukin-6 antagonists (p < 0.0001). Multivariable analyses adjusted for imbalanced prognostic factors confirmed the UK cohort to be characterised by worse risk of death at 30 days and 6 months, independent of patient's age, gender, tumour stage and status, number of co-morbidities, Covid-19 severity, receipt of anti-cancer and anti-Covid-19 therapy. Rates of permanent cessation of anti-cancer therapy post Covid-19 were similar in UK versus EU. Conclusions: UK cancer patients have been more severely impacted by the unfolding of the Covid-19 pandemic despite societal risk mitigation factors and rapid deferral of anti-cancer therapy. The increased frailty of UK cancer patients highlights high-risk groups that should be prioritised for anti-SARS-Cov-2 vaccination. Continued evaluation of long-term outcomes is warranted.
ABSTRACT
Background: cancer have been reported to experience severe complications and poor outcomes to severe acute respiratory syndrome coronavirus 2 (SARSCoV-2)-related disease (COVID-19). Anti-SARS-CoV-2 immunoglobulin-G (IgG) can be detected within three weeks after infection. However, scant information is available on the seroconversion rates of patients with cancer and COVID-19. Material: This is a multicenter, observational, prospective study that enrolled patients and oncology health professionals with SARS-CoV-2 infection confirmed by RT-PCR assay, patients and oncology health professionals with clinical or radiological suspicious of infection by SARS-CoV-2, and patients with cancer who are considered at high risk for infection. All subjects were tested with the 2019-nCoV IgG/IgM Rapid Test Cassett, which is a qualitative membrane-based immunoassay for the detection of IgG and IgM antibodies to SARS-CoV-2. The aim of the study was to evaluate anti-SARS-CoV-2 seroconversion rate in patients with cancer and healthcare professionals with confirmed or clinically suspected COVID-19. Results: Between March 30 and May 11, 2020, 166 subjects were enrolled in the study. Cancer patients and health workers were 61 (36.7%) and 105 (63.3%), respectively. Seventyfour subjects (44.6%) had confirmed SARS-CoV-2 diagnosis by RT-PCR testing on nasopharyngeal swab specimen, while 49 (29.5%) had a clinical suspicious of COVID-19 in absence of RT-PCR confirmation. Median time between symptom onset/ RT-PCR confirmation to serum antibody test was 17 days (IQR, 26). Considering the population with confirmation by RT-PCR, 83.8% was IgG positive. Neither differences in terms of IgG positivity rate nor in median time from SARS-CoV-2 diagnosis to IgG detection were observed between cancer patients and health workers (87.9% vs 80.5%;P=0.39;23.0 vs 28.0 days;P=0.21). Conclusions: Our data indicate that SARS-CoV-2-specific IgG antibody detection does not differ between cancer patients and healthy subjects. Fast test for antibody detection can be complementary to RNA RT-PCR testing for the diagnosis of COVID-19 in this vulnerable patient population.
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Background: Endocrine therapy (ET) represents the mainstay of adjuvant treatment for hormone receptor positive (HR+) early breast cancer (EBC). Currently, international guidelines recommend the use of ovarian function suppression (OFS) plus aromatase inhibitors (AIs) as preferred choice in intermediate/high-risk premenopausal patients, according to SOFT and TEXT study results. In the last years, several studies investigated the role of adjuvant ET (AET) extension beyond the first 5 years, globally demonstrating a reduction in the rate of disease relapse, particularly in high-risk patients. However, the vast majority of trials exploring AIs extension included postmenopausal women only. Therefore, compelling evidence supporting the extension of AET with AIs in premenopausal patients is currently missing. The aim of the present study was to reach an Italian expert consensus on the extended AET in premenopausal patients. Material and methods: Firstly, a Steering Committee defined relevant statements on the topic. Subsequently, a panel of 8 Italian oncologists with expertise in breast cancer participated in this Delphi consensus study in January 2020. According to the Delphi method, experts voted anonymously each statement, expressing their level of agreement using a five point Likert scale. For each statement, the consensus was reached if either the sum of negative or positive answers exceeded 66%. Currently, the study has been extended to additional 12 Italian oncologists, using a web-based format, due to the COVID-19 pandemic. Altogether, the 20 participants represent oncological institutions distributed over the country. Results: A total of 44 statements were defined and voted to gain consensus. The statements concerned clinical, pathological and genomic factors that could be used to assess the utility, the type (AIs vs. tamoxifen) and the duration (2-2.5 vs. 5 years) of extended AET in premenopausal patients. The consensus reached on each statement will be presented during the congress. Conclusions: Intermediate/high-risk premenopausal EBC patients are likely to benefit from extended AET, although studies specifically designed in premenopausal setting are still missing. In the lack of direct evidence, this methodologically sound expert consensus may guide practicing oncologists in the choice of the best treatment and duration based on clinical, pathological and genomic information.
ABSTRACT
BACKGROUND: Patients with cancer have high risk for severe complications and poor outcome to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related disease [coronavirus disease 2019 (COVID-19)]. Almost all subjects with COVID-19 develop anti-SARS-CoV-2 immunoglobulin G (IgG) within 3 weeks after infection. No data are available on the seroconversion rates of cancer patients and COVID-19. PATIENTS AND METHODS: We conducted a multicenter, observational, prospective study that enrolled (i) patients and oncology health professionals with SARS-CoV-2 infection confirmed by real-time RT-PCR assays on nasal/pharyngeal swab specimens; (ii) patients and oncology health professionals with clinical or radiological suspicious of infection by SARS-CoV-2; and (iii) patients with cancer who are considered at high risk for infection and eligible for active therapy and/or major surgery. All enrolled subjects were tested with the 2019-nCoV IgG/IgM Rapid Test Cassette, which is a qualitative membrane-based immunoassay for the detection of IgG and IgM antibodies to SARS-CoV-2. The aim of the study was to evaluate anti-SARS-CoV-2 seroconversion rate in patients with cancer and oncology health care professionals with confirmed or clinically suspected COVID-19. RESULTS: From 30 March 2020 to 11 May 2020, 166 subjects were enrolled in the study. Among them, cancer patients and health workers were 61 (36.7%) and 105 (63.3%), respectively. Overall, 86 subjects (51.8%) had confirmed SARS-CoV-2 diagnosis by RT-PCR testing on nasopharyngeal swab specimen, and 60 (36.2%) had a clinical suspicious of COVID-19. Median time from symptom onset (for cases not confirmed by RT-PCR) or RT-PCR confirmation to serum antibody test was 17 days (interquartile range 26). In the population with confirmed RT-PCR, 83.8% of cases were IgG positive. No difference in IgG positivity was observed between cancer patients and health workers (87.9% versus 80.5%; P = 0.39). CONCLUSIONS: Our data indicate that SARS-CoV-2-specific IgG antibody detection do not differ between cancer patients and healthy subjects.
Subject(s)
COVID-19 , Neoplasms , Antibodies, Viral , Health Personnel , Humans , Immunoglobulin M , Neoplasms/epidemiology , Prospective Studies , SARS-CoV-2 , Sensitivity and Specificity , SeroconversionABSTRACT
Background: Poor outcomes for patients with cancer and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related disease (COVID-19) have been reported so far. Although anti-SARS-CoV-2 IgG response is usually detectable within three weeks after infection, limited information on the seroconversion rate of patients with cancer infected by SARS-CoV-2 is available. Methods: This is a multicenter, observational, prospective study that included patients and oncology healthcare workers (HCWs) with SARS-CoV-2 infection confirmed by RT-PCR or clinical/radiological suspicious of infection as well as patients with cancer who are considered at high risk for infection. All subjects were tested with the 2019-nCoV IgG/IgM Rapid Test Cassett for the fast detection of IgG and IgM antibodies against SARS-CoV-2. The aim of the study was to evaluate anti-SARS-CoV-2 seroconversion rates by qualitative assay in patients with cancer and HCWs with confirmed or clinically suspected COVID-19. Results: At first interim analysis, 166 subjects were enrolled in the study. Cancer patients and HCWs were 61 (36.7%) and 105 (63.3%), respectively. HCWs were younger than patients with cancer (median age 41 vs 62 years;P<0.001). Eighty-six subjects (51.8%) had confirmed SARS-CoV-2 diagnosis by RT-PCR testing on nasopharyngeal swab specimen, while forty-nine (29.5%) had a clinical suspicious of COVID-19 in absence of RT-PCR confirmation. In patients with RT-PCR-confirmed SARS-CoV-2 infection, 62 (83.8%) were IgG-positive. Neither differences in terms of IgG positivity (87.9% vs 80.5%;P=0.39) nor in median time from COVID-19 diagnosis to IgG detection (23.0 vs 28.0 days;P=0.21) were found between patients with cancer and HCWs. Conclusions: Our data show that SARS-CoV-2-specific IgG antibody response is not different between cancer patients and healthy subjects. Qualitative rapid test for antibody detection represents an useful support to RNA RT-PCR testing for the diagnosis of COVID-19 in high-risk populations, including patients with cancer. Legal entity responsible for the study: Istituto Europeo di Oncologia IRCCS. Funding: This work was partially supported by the Italian Ministry of Health with Ricerca Corrente and 5x1000 funds. MEDnoTE srl (Spin-off of University of Trieste) supported the present study by providing the rapid test used for anti-SARS-CoV-2 antibody detection. Disclosure: D.G. Generali: Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Novartis, Pfizer, Lilly. G. Curigliano: Speaker Bureau/Expert testimony: MSD;Advisory/Consultancy: Mylan, Daichii Sankyo;Advisory/Consultancy, Speaker Bureau/Expert testimony: Lilly, Pfizer, Merck, Foundation Medicine, Samsung, Celltrion;Advisory/Consultancy, Speaker Bureau/Expert testimony: Seattle Genetics, Nanostring;Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche;Speaker Bureau/Expert testimony: Novartis, BMS;Honoraria (self): Ellipsis. All other authors have declared no conflicts of interest.
ABSTRACT
Background: The ongoing SARS-CoV-2 pandemic and ensuing coronavirus disease (COVID-19) is challenging cancer care and services worldwide. Methods: A 95 items survey was distributed worldwide by 20 oncologists from 10 of the most affected countries in order to evaluate the impact on organization of oncological care. Results: 109 representatives from oncology centers in 18 countries (62.4% academic hospitals) filled out the survey (June 17 – July 14, 2020). A swab or gargle test is systematically performed before day care unit or overnight stay admissions in 27.5% and 58.7% of the centers, respectively. A local registry (64.2%) and systematic tracing (77.1%) of infected patients was organized in many centers. Treatment modalities mostly affected by the pandemic (cancellation/delay) were surgery (44.1%) and chemotherapy (25.7%). Earlier cessation of palliative treatment was observed in 32.1% of centers, and 64.2 % of participants agree that under-treatment is a major concern. At the pandemic peak, teleconsultations were performed for follow-up (94.5%), for oral therapy (92.7%), but also for patients receiving immunotherapy (57.8%) or chemotherapy (55%). Approximately 82% of participants estimate that they will continue to use telemedicine. Most participants reported more frequent use of virtual tumor boards (82%) and oncological team meetings (92%), but 45% disagree that virtual meetings are an acceptable alternative to live international meetings. Although 60.9% report reduced clinical activity during the pandemic peak, only 28.4% had an increased scientific activity. Only 18% of participants estimate that their well-being will not recover to previous levels by the end of the year;63% indicate easily accessible psychological support for caregivers, but only 10% used or planned to use it. All clinical trial activities are or will soon be reactivated in 72.5% of the centers. Major study protocol violations/deviations were observed in 27.5% and significant reductions of clinical trial activities are expected by 37% of centers this year. Conclusions: COVID-19 has a major impact on organization of patient care, well-being of caregivers, continued medical education and clinical trial activities in oncology. Legal entity responsible for the study: The authors. Funding: Fondation Léon Fredericq. Disclosure: G. Jerusalem: Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Novartis;Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Roche;Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Pfizer;Advisory/Consultancy, Travel/Accommodation/Expenses: Lilly;Advisory/Consultancy, Travel/Accommodation/Expenses: Amgen;Advisory/Consultancy, Travel/Accommodation/Expenses: BMS;Advisory/Consultancy, Travel/Accommodation/Expenses: AstraZeneca;Advisory/Consultancy, Travel/Accommodation/Expenses: Daiichi Sankyo;Advisory/Consultancy: AbbVie;Travel/Accommodation/Expenses: MedImmune;Travel/Accommodation/Expenses: Merck KGaA. G. Curigliano: Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche;Advisory/Consultancy, Speaker Bureau/Expert testimony: Seattle Genetics;Speaker Bureau/Expert testimony, Writing engagement: Novartis;Advisory/Consultancy, Speaker Bureau/Expert testimony: Lilly;Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer;Advisory/Consultancy, Speaker Bureau/Expert testimony: Foundation Medicine;Advisory/Consultancy, Speaker Bureau/Expert testimony: Samsung;Advisory/Consultancy, Speaker Bureau/Expert testimony: Celltrion;Leadership role, Scientific Affairs Group: Ellipsis;Speaker Bureau/Expert testimony, Writing engagement: BMS;Speaker Bureau/Expert testimony: MSD;Advisory/Consultancy: Mylan. M. Campone: Honoraria (self), Advisory/Consultancy: GT1;Honoraria (institution), Advisory/Consultancy: Sanofi;Honoraria (institution), Advisory/Consultancy: Pierre-Favre;Honoraria (institution), Advisory/Consultancy: AstraZeneca;Honoraria (institution), Advisory/Consultancy: Servi r;Honoraria (institution), Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis;Honoraria (institution), Advisory/Consultancy: AbbVie;Honoraria (institution), Advisory/Consultancy: Accord;Honoraria (institution), Advisory/Consultancy: Pfizer;Speaker Bureau/Expert testimony: Lilly. M. Martin: Advisory/Consultancy, Research grant/Funding (institution): Roche;Advisory/Consultancy, Research grant/Funding (institution): Novartis;Advisory/Consultancy, Research grant/Funding (institution): Puma;Advisory/Consultancy: AstraZeneca;Advisory/Consultancy: Amgen;Advisory/Consultancy: Taiho Oncology;Advisory/Consultancy: Daichii Sankyo;Advisory/Consultancy: PharmaMar;Advisory/Consultancy: Eli Lilly;Advisory/Consultancy: Pfizer. M. Cristofanilli: Advisory/Consultancy: CytoDyn;Advisory/Consultancy, Speaker Bureau/Expert testimony, Research grant/Funding (institution): Pfizer;Advisory/Consultancy: Lilly;Advisory/Consultancy: Novartis;Advisory/Consultancy, Speaker Bureau/Expert testimony: Foundation Medicine;Advisory/Consultancy: G1 Therapeutics;Advisory/Consultancy: Sermionexx;Advisory/Consultancy: Genentch. L. Pusztai: Honoraria (self), Research grant/Funding (institution), Clinical trial support: Merck;Honoraria (self), Research grant/Funding (institution), Clinical trial support: AstraZeneca;Honoraria (self), Research grant/Funding (institution), Clinical trial support: Seattle Genetics;Honoraria (self): Novartis;Honoraria (self), Research grant/Funding (institution), Clinical trial support: Roche Genentech;Honoraria (self): Eisai;Honoraria (self): Daiichi;Honoraria (self): Syndax;Honoraria (self): Immunomedics. R. Bartsch: Advisory/Consultancy: Accord;Honoraria (self): AstraZeneca;Advisory/Consultancy, Research grant/Funding (institution): Daiichi;Advisory/Consultancy, Travel/Accommodation/Expenses: Eli-Lilly;Advisory/Consultancy, Travel/Accommodation/Expenses: MSD;Advisory/Consultancy, Research grant/Funding (institution): Novartis;Advisory/Consultancy, Research grant/Funding (institution): Roche;Advisory/Consultancy: Puma;Advisory/Consultancy: Pierre-Favre;Advisory/Consultancy: Sandoz;Advisory/Consultancy: Eisai. M. Tagliamento: Travel/Accommodation/Expenses: Roche;Travel/Accommodation/Expenses: Bristol-Myers Squibb;Travel/Accommodation/Expenses: AstraZeneca;Travel/Accommodation/Expenses: Takeda;Travel/Accommodation/Expenses: Novartis;Travel/Accommodation/Expenses: Amgen. J. Cortés: Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Roche;Honoraria (self), Advisory/Consultancy: Celgene;Advisory/Consultancy: Cellestia;Advisory/Consultancy, Research grant/Funding (institution): AstraZeneca;Advisory/Consultancy: Biothera Pharmaceutical;Advisory/Consultancy: Merus;Advisory/Consultancy: Seattle Genetics;Honoraria (self), Advisory/Consultancy, Travel/Accommodation/Expenses: Daiichi Sankyo;Advisory/Consultancy: Erytech;Advisory/Consultancy: Athenex + Polyphor;Advisory/Consultancy, Shareholder/Stockholder/Stock options: MedSIR;Honoraria (self), Advisory/Consultancy: Lilly;Advisory/Consultancy: Servier;Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution): Merck Sharp Dome;Advisory/Consultancy: GSK;Advisory/Consultancy: Leuko;Advisory/Consultancy: Bioasis;Advisory/Consultancy: Clovis Oncology;Advisory/Consultancy: Boehringer Ingelheim;Honoraria (self), Travel/Accommodation/Expenses: Novartis;Honoraria (self), Travel/Accommodation/Expenses: Eisai;Honoraria (self), Research grant/Funding (institution), Travel/Accommodation/Expenses: Pfizer;Honoraria (self): Samsung Bioepis;Research grant/Funding (institution): Ariad Pharmaceuticals;Research grant/Funding (institution): Baxalta GMBH/Servier Affaires;Research grant/Funding (institution): Bayer Healthcare;Research grant/Funding (institution): F. Hoffmann-La Roche;Research grant/Funding (institution): Guardanth Health;Research grant/Funding (institution): Piqur THerapeutics;Research grant/Funding (institution): Puma C;Research grant/ unding (institution): Queen Mary University of London. E.M. Ciruelos: Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche;Advisory/Consultancy, Speaker Bureau/Expert testimony: Lilly;Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis;Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Pfizer. H.S. Rugo: Research grant/Funding (institution): Eisai;Research grant/Funding (institution): Genentech;Research grant/Funding (institution): Lilly;Research grant/Funding (institution), Travel/Accommodation/Expenses: MacroGenics;Research grant/Funding (institution): Merck;Research grant/Funding (institution), Travel/Accommodation/Expenses: Novartis;Research grant/Funding (institution): Obi Pharma;Research grant/Funding (institution): Odonate Therapeutics;Research grant/Funding (institution): Immunomedics;Research grant/Funding (institution), Travel/Accommodation/Expenses: Daiichi-Sankyo;Research grant/Funding (institution), Travel/Accommodation/Expenses: Pfizer;Advisory/Consultancy: Samsung;Advisory/Consultancy: Celtrion;Travel/Accommodation/Expenses: Mylan;Travel/Accommodation/Expenses: AstraZeneca. All other authors have declared no conflicts of interest.