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.
ABSTRACT
Background: The long-term impact of COVID-19 in cancer patients (pts) is undefined. Methods: Among 2795 consecutive pts with COVID-19 and cancer registered to OnCovid between 01/2020 and 02/2021, we examined clinical outcomes of pts reassessed post COVID-19 recovery. Results: Among 1557 COVID-19 survivors, 234 (15%) reported sequelae including respiratory symptoms (49.6%), fatigue (41%) and cognitive/psychological dysfunction (4.3%). Persisting COVID-19 sequelae were more likely found in males (p=0.0407) aged ≥65 years (p=0.0489) with ≥2 comorbidities (p=0.0006) and positive smoking history (p=0.0004). Sequelae were associated with history of prior hospitalisation (p<0.0001), complicated disease (p<0.0001) and COVID-19 therapy (p=0.0002). With a median post-COVID-19 follow up of 128 days (95%CI 113-148), multivariable analysis of survival revealed COVID-19 sequelae to be associated with an increased risk of death (HR 1.76, 95%CI 1.16-2.66) after adjusting for sex, age, comorbidities, tumour characteristics, anticancer therapy and COVID-19 severity. Out of 473 patients who were on systemic anticancer therapy (SACT) at COVID-19 diagnosis;62 (13.1%) permanently discontinued therapy and 75 (15.8%) received SACT adjustments, respectively. Discontinuations were due to worsening performance status (45.1%), disease progression (16.1%) and residual organ disfunction (6.3%). SACT adjustments were pursued to avoid hospital attendance (40%), prevent immunosuppression (57.3%) or adverse events (20.3%). Multivariable analyses showed permanent discontinuation to be associated with an increased risk of death (HR 4.2, 95%CI: 1.62-10.7), whereas SACT adjustments did not adversely affect survival. Conclusions: Sequelae post-COVID-19 affect up to 15% of patients with cancer and adversely influence survival and oncological outcomes after recovery. SACT adjustments can be safely pursued to preserve oncological outcomes in patients who remain eligible to treatment.
ABSTRACT
Background: The long-term impact of COVID-19 in cancer patients (pts) is undefined. Methods: Among 2795 consecutive pts with COVID-19 and cancer registered to OnCovid between 01/2020 and 02/2021, we examined clinical outcomes of pts reassessed post COVID-19 recovery. Results: Among 1557 COVID-19 survivors, 234 (15%) reported sequelae including respiratory symptoms (49.6%), fatigue (41%) and cognitive/psychological dysfunction (4.3%). Persisting COVID-19 sequelae were more likely found in males (p=0.0407) aged ≥65 years (p=0.0489) with ≥2 comorbidities (p=0.0006) and positive smoking history (p=0.0004). Sequelae were associated with history of prior hospitalisation (p<0.0001), complicated disease (p<0.0001) and COVID-19 therapy (p=0.0002). With a median post-COVID-19 follow up of 128 days (95%CI 113-148), multivariable analysis of survival revealed COVID-19 sequelae to be associated with an increased risk of death (HR 1.76, 95%CI 1.16-2.66) after adjusting for sex, age, comorbidities, tumour characteristics, anticancer therapy and COVID-19 severity. Out of 473 patients who were on systemic anticancer therapy (SACT) at COVID-19 diagnosis;62 (13.1%) permanently discontinued therapy and 75 (15.8%) received SACT adjustments, respectively. Discontinuations were due to worsening performance status (45.1%), disease progression (16.1%) and residual organ disfunction (6.3%). SACT adjustments were pursued to avoid hospital attendance (40%), prevent immunosuppression (57.3%) or adverse events (20.3%). Multivariable analyses showed permanent discontinuation to be associated with an increased risk of death (HR 4.2, 95%CI: 1.62-10.7), whereas SACT adjustments did not adversely affect survival. Conclusions: Sequelae post-COVID-19 affect up to 15% of patients with cancer and adversely influence survival and oncological outcomes after recovery. SACT adjustments can be safely pursued to preserve oncological outcomes in patients who remain eligible to treatment. Clinical trial identification: NCT04393974. Legal entity responsible for the study: Imperial College London. Funding: Has not received any funding. Disclosure: A. Cortellini: Financial Interests, Personal, Advisory Board: MSD;Financial Interests, Personal, Advisory Board: BMS;Financial Interests, Personal, Advisory Board: Roche;Financial Interests, Personal, Invited Speaker: Novartis;Financial Interests, Personal, Invited Speaker: AstraZeneca;Financial Interests, Personal, Invited Speaker: Astellas;Financial Interests, Personal, Advisory Board: Sun Pharma. D.J. Pinato: Financial Interests, Personal, Advisory Board: ViiV Healthcare;Financial Interests, Personal, Invited Speaker: Bayer;Financial Interests, Personal, Advisory Board: Eisai;Financial Interests, Personal, Invited Speaker: Roche;Financial Interests, Personal, Invited Speaker: AstraZeneca. All other authors have declared no conflicts of interest.
ABSTRACT
Background: Around 15% of adult GIST are wild type for KIT/PDGFRA mutations (KPWT), usually have SDH deficiencies, and are resistant to imatinib (IM). The underlying mechanisms include overexpression of HIF1α in SDH deficient-GIST, high IGFR signaling through MAPK, BRAF mutation or STAT3 activation. Regorafenib (RE), targeting these pathways, could be more active as upfront therapy in KPWT GIST. Methods: Patients (pts) >18, with advanced non pretreated KPWT GIST were eligible after central confirmation by next-generation sequencing (NGS). Eligible pts received RE at 160mg/d for 21/28d cycles. Primary end-point was disease control rate (DCR) at 12 weeks (RECIST 1.1 ) by central radiological assessment (CRA). Secondary objectives were PFS, OS, ORR (RECIST,Choi), safety and QoL. An amendment allowed previous IM (adjuvant). Statistical assumptions [H0 73% and H1 90% (α 0.1 and β 0.2)], defined a sample size of 20 pts. Results: From May 2016 to October 2020, 30pts with KPWT GIST (by Sanger) underwent central molecular screening. Among the 15 non-eligible pts, 8 harbored KIT exon 11 mutations, 3 exon 9 and 3 PDGFRA exon 18 by NGS. The remaining 16 (53.3%) molecularly eligible pts were enrolled and started RE except one pt due to COVID-19 pandemic. The trial was prematurely closed due to low recruitment, especially after COVID outbreak. Demographics and treatment details in the table. Based on CRA, 12w-DCR was 86.7%. With a median (m) FU of 26 (5-44) months (mo), 10/15 pts progressed, with a mPFS of 10.8 mo (95% CI 6.9-14.8). 6 mo, 9 mo and 12 mo PFS rates were 65%, 48% and 29% respectively. 2 pts were PD-free at 25 and 43 mo from start of RE. 6/15 pts died, with a mOS of 33.5 mo (95% CI NR). [Formula presented] Conclusions: The study results approach the prespecified activity threshold. The low recruitment rate could have affected this attainment. Other analysis of secondary endpoints are ongoing. The high percentage of overlooked mutant GIST by Sanger raises the need of NGS in presumed KPWT GIST. Clinical trial identification: NCT02638766. Legal entity responsible for the study: Spanish Group for Research on Sarcoma (GEIS). Funding: Bayer. Disclosure: J. Martin Broto: Financial Interests, Personal, Expert Testimony, Honoraria: Lilly;Financial Interests, Personal, Expert Testimony, Honoraria: PharmaMar;Financial Interests, Personal, Expert Testimony, Honoraria: Eisai;Financial Interests, Personal, Expert Testimony, Honoraria: Bayer;Financial Interests, Personal, Invited Speaker: PharmaMar;Financial Interests, Institutional, Invited Speaker: PharmaMar;Financial Interests, Institutional, Invited Speaker: Eisai;Financial Interests, Institutional, Invited Speaker: Novartis;Financial Interests, Institutional, Invited Speaker: IMMIX Biopharma;Financial Interests, Institutional, Invited Speaker: Lixte;Financial Interests, Institutional, Invited Speaker: Karyopharm;Financial Interests, Institutional, Invited Speaker: Bayer;Financial Interests, Institutional, Invited Speaker: Celgene;Financial Interests, Institutional, Invited Speaker: Pfizer;Financial Interests, Institutional, Invited Speaker: BMS;Financial Interests, Institutional, Invited Speaker: Blueprint;Financial Interests, Institutional, Invited Speaker: Deciphera;Financial Interests, Institutional, Invited Speaker: Nektar;Financial Interests, Institutional, Invited Speaker: FORMA;Financial Interests, Institutional, Invited Speaker: Amgen;Financial Interests, Institutional, Invited Speaker: Daiichi Sankyo;Financial Interests, Institutional, Invited Speaker: Lilly;Financial Interests, Institutional, Invited Speaker: AROG;Financial Interests, Institutional, Invited Speaker: Adaptimmune;Financial Interests, Institutional, Invited Speaker: GSK. N. Hindi: Financial Interests, Personal, Invited Speaker: PharmaMar;Financial Interests, Personal, Advisory Board: PharmaMar;Financial Interests, Institutional, Research Grant: PharmaMar;Financial Interests, Institutional, Sponsor/Funding: PharmaMar;Financial Interests, Institutional, Research Grant: Nova tis;Financial Interests, Institutional, Research Grant: Eisai;Financial Interests, Institutional, Research Grant: Immix Bio;Financial Interests, Institutional, Sponsor/Funding: Bayer;Financial Interests, Institutional, Sponsor/Funding: Deciphera;Financial Interests, Institutional, Sponsor/Funding: Daychii;Financial Interests, Institutional, Sponsor/Funding: Blueprint;Financial Interests, Institutional, Sponsor/Funding: Adaptimmune;Financial Interests, Institutional, Sponsor/Funding: GSK;Financial Interests, Institutional, Sponsor/Funding: Karyopharm;Financial Interests, Institutional, Sponsor/Funding: Celgene;Financial Interests, Institutional, Sponsor/Funding: AROG. J. Lavernia: Financial Interests, Personal, Invited Speaker: PharmaMar;Financial Interests, Personal, Invited Speaker: BMS. C. Serrano: Financial Interests, Personal, Invited Speaker: Bayer;Financial Interests, Institutional, Research Grant: Bayer. D. Moura: Financial Interests, Institutional, Research Grant: Novartis;Financial Interests, Institutional, Research Grant: Eisai;Financial Interests, Institutional, Research Grant: PharmaMar;Financial Interests, Institutional, Research Grant: Immix Bio. J. Blay: Financial Interests, Institutional, Research Grant: Bayer;Financial Interests, Personal, Invited Speaker: Bayer;Financial Interests, Institutional, Research Grant: Novartis;Financial Interests, Personal, Invited Speaker: Novartis;Financial Interests, Institutional, Research Grant: Roche;Financial Interests, Personal, Invited Speaker: Roche;Financial Interests, Institutional, Research Grant: Deciphera;Financial Interests, Personal, Research Grant: Deciphera. E.R. Fumagalli: Financial Interests, Institutional, Research Grant: Bayer. All other authors have declared no conflicts of interest.