15-Month Attributes of Post-Covid Syndrome in Therapeutically Vaccinated Outpatients

Background: In the third year of the coronavirus disease 2019 (COVID-19) pandemic, long-term post-COVID syndrome (PCS) following severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infections poses the significant challenge for patients and health systems globally. Whilst COVID-19 vaccinations prior to SARS-CoV-2 infection reduce the risk of PCS, the role of therapeutic vaccination in PCS recovery remains controversial. We present a 15 months longitudinal, prospective observational cohort study to examine long-term clinical courses, PCS recovery with and without vaccination as well as humoral immune responses in initially unvaccinated PCS patients. Method(s): A total of 227 COVID-19 convalescents of our initial mild COVID-19 outpatient cohort (N=958) from which longitudinal data was available were included in this study. PCS was defined according to the WHO definition. 76.7% (174/227) of individuals received at least one vaccination between 10 and 15 months after first SARS-CoV-2 infection. Receptor binding domain (RBD)- specific SARS-CoV-2 immunoglobulin G (IgG) and distinct symptom phenotypes (P) were longitudinally assessed for 15 months. Using binomial regression models, odds ratios (OR) with 95% confidence interval (95%CI) of descriptive, longitudinal variables associated with long-term PCS were calculated. Result(s): 35.8% (82/227) and 31.3% (71/227) of patients had PCS at months 10 and 15 (figure 1A). SARS-CoV-2 IgG titers were equally distributed over time among age groups, sex, and PCS. PCS occurred in 30.5% (53/174) of vaccinated and 34.0% (18/53) of unvaccinated patients. Between 6 and 10 months (DELTAT2/T3: not yet vaccinated) and 10 and 15 months (DELTAT3/T4: vaccinated) after symptom onset (figure 1B), a comparable fraction of PCS patients recovered (DELTAT2/T3: 22.5% and DELTAT3/T4: 20.0%). Fatigue/dyspnea (P2) and not anosmia/ageusia (P1) constituted PCS at month 15 (P2 23.9% versus P1 1.4%). Headache (P4) and diarrhea (P5) at baseline were risk factors for PCS at months 15, respectively (P4: OR 2.01 (95%CI 1.11-3.52), p= .018;P5: OR 3.01(95%CI 1.44-5.94), p= .002). Conclusion(s): Our results indicate, that distinct symptom phenotypes can constitute and predict long-term PCS 15 months after mild COVID. Recovery of PCS was observed similarly in both therapeutically vaccinated and unvaccinated patients. Thus, development of targeted PCS therapeutics is needed to improve patient care and future epidemiological investigations. (Figure Presented).

COVID-19 in cancer patients - higher inflammatory response in patients with active cancer

Background: Active cancer has been identified as an independent risk factor for severity and mortality in COVID-19. However, direct comparisons of SARS-CoV-2 infected patients (pts) with active and non-active cancers remain scarce. Method(s): We retrospectively analyzed a cohort of pts with cancer with confirmed SARS-CoV-2 infection, enrolled 03/16/2020 - 07/31/2021. Data on demographics, cancer and laboratory findings were collected. Descriptive and subsequent regression analysis was performed. Endpoints were progression to severe COVID-19 and infection-associated mortality. Result(s): In total, 987 pts with cancer (510 active vs 477 non-active) were included in our analysis. Majority was male and > 55 years, with a higher number of elderly pts with non-active cancer. CCI was 4.75 vs 3.85 in pts with active and non-active cancer (p<0.001). Localized solid tumors were reported in 38 vs 79% (p<0.001), metastasized in 37.5 vs 5.5% (p<0.001) and hematological diseases in 37.5 vs 19.5% (p<0.001) pts with active and non-active cancer, respectively. At virus detection, majority of pts showed mild to moderate symptoms, while deterioration to severe COVID-19 was slightly more common in pts with active cancer (19% vs 16%;p=0.284). COVID-19 related mortality was significantly higher in pts with active cancer (24% vs 17.5%, p<0.001). In line, severe cytopenia and an increase of inflammatory markers were common findings in pts with active cancer at baseline, particularly in those who developed severe infection or died. Multivariate analysis revealed that ferritin (14.24 [2.1-96], p=0.006) and CRP (2.85 [1.02-8.02], p=0.046) were associated with severe COVID-19 and infection-related mortality. In pts with non-active cancer, association was seen for ferritin only (4.1 [1.51-11.17], p=0.006). Conclusion(s): Comparing pts with active and non-active cancer, mortality rate was significantly higher in pts with active cancer. Also inflammatory markers were significantly increased assuming higher levels of inflammation may play a role in adverse outcome of COVID-19 in pts with active cancer.

External Validation of the 4C Mortality Score and the qSOFA for Different Variants of Concerns of SARS-CoV-2 Using Data of the NAPKON Cross-Sectoral Cohort Platform (SUEP)

Background. Numerous predictive clinical scores with varying discriminatory performance have been developed in the context of the current coronavirus disease 2019 (COVID-19) pandemic. To support clinical application, we test the transferability of the frequently applied 4C mortality score (4C score) to the German prospective Cross-Sectoral Platform (SUEP) of the National Pandemic Cohort Network (NAPKON) compared to the non COVID-19 specific quick sequential organ failure assessment score (qSOFA). Our project aims to externally validate these two scores, stratified for the most prevalent variants of concerns (VOCs) of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) in Germany. Methods. A total of 685 adults with polymerase chain reaction (PCR)-detected SARS-CoV-2 infection were included from NAPKON-SUEP. Patients were recruited from 11/2020 to 03/2022 at 34 university and non-university hospitals across Germany. Missing values were complemented using multiple imputation. Predictive performance for in-hospital mortality at day of baseline visit was determined by area under the curve (AUC) with 95%-confidence interval (CI) stratified by VOCs of SARS-CoV-2 (alpha, delta, omicron) (Figure 1). Figure 1: Study flow chart with inclusion criteria and methodological workflow. Results. Preliminary results suggest a high predictive performance of the 4C score for in-hospital mortality (Table 1). This applies for the overall cohort (AUC 0.813 (95%CI 0.738-0.888)) as well as the VOC-strata (alpha: AUC 0.859 (95%CI 0.748-0.970);delta: AUC 0.769 (95%CI 0.657-0.882);omicron: AUC 0.866 (95%CI 0.724-1.000)). The overall mortality rates across the defined 4C score risk groups are 0.3% (low), 3.2% (intermediate), 11.6% (high), and 49.5% (very high). The 4C score performs significantly better than the qSOFA (Chi2-test: p=0.001) and the qSOFA does not seem to be a suitable tool in this context. Table 1: Discriminatory performance of the 4C Mortality Score and the qSOFA score within the validation cohort NAPKON-SUEP stratified by the Variant of Concerns of SARS-CoV- 2. Conclusion. Despite its development in the early phase of the pandemic and improved treatment, external validation of the 4C score in NAPKON-SUEP indicates a high predictive performance for in-hospital mortality across all VOCs. However, since the qSOFA was not specifically designed for this predictive issue, it shows low discriminatory performance, as in other validation studies. Any interpretations regarding the omicron stratum are limited due to the sample size.

Primary analysis of MOUNTAINEER: A phase 2 study of tucatinib and trastuzumab for HER2-positive mCRC

Background: Despite the occurrence of HER2 amplification/overexpression (HER2+) in ~3% to 5% of all patients with metastatic colorectal cancer (mCRC) and up to ~10% of patients with RAS/BRAF wild-type mCRC, there are currently no FDA- or EMA-approved HER2-directed therapies for HER2+ mCRC. Patients with mCRC who progress on early lines of chemotherapy regimens receive limited clinical benefit from current standard-of-care treatments. Tucatinib is a highly selective, HER2-directed, tyrosine kinase inhibitor. The MOUNTAINEER trial (NCT03043313) was initiated to evaluate the efficacy and safety of the investigational combination of tucatinib with trastuzumab in patients with HER2+ mCRC. Here we present results from the primary analysis of MOUNTAINEER. Methods: MOUNTAINEER is a multi-center, open-label, randomised, phase 2 trial conducted in the US and Europe. Eligible patients had HER2+ (one or more local tests: 3+ immunohistochemistry, 2+ immunohistochemistry with amplification by in situ hybridization, or amplification by next‑generation sequencing of tumor tissue) and RAS wild-type mCRC with progression on or intolerance to fluoropyrimidine, oxaliplatin, irinotecan, and an anti-VEGF antibody. Measurable disease and an ECOG performance status of 0–2 were required. Previous HER2-directed therapies were not permitted. The trial initially consisted of a single cohort (Cohort A) to be treated with tucatinib (300 mg PO BID) and trastuzumab (8 mg/kg IV then 6 mg/kg IV every 3 weeks). The trial was expanded to include patients randomised 4:3 to receive tucatinib + trastuzumab (Cohort B) or tucatinib monotherapy (Cohort C). The primary endpoint is confirmed objective response rate (ORR) per RECIST 1.1 by blinded independent central review (BICR) in Cohorts A+B. Secondary endpoints include duration of response (DOR), progression-free survival (PFS), overall survival (OS), and safety and tolerability. Results: MOUNTAINEER enrolled 117 patients between 08Aug2017 and 22Sept2021. Data cutoff was 28Mar2022. The median age was 56.0 years (range, 24, 77), and baseline characteristics were balanced across cohorts. Eighty-six patients received at least 1 dose of study treatment in Cohorts A+B, and 30 patients received tucatinib monotherapy in Cohort C (total, 116). The overall median duration of follow-up was 16.3 months (IQR, 10.8, 28.2). In Cohorts A+B, the confirmed ORR by BICR was 38.1% (95% CI, 27.7, 49.3). The median DOR was 12.4 months (95% CI, 8.5, 20.5). The median PFS was 8.2 months (95% CI, 4.2, 10.3), and the median OS was 24.1 months (95% CI, 20.3, 36.7). The most common adverse events (AEs) in Cohorts A+B were diarrhoea (64.0%), fatigue (44.2%), nausea (34.9%), and infusion-related reaction (20.9%);the most common AE of grade ≥3 was hypertension (7.0%). Adverse events leading to tucatinib discontinuation in Cohorts A+B occurred in 5.8% of patients and included alanine amino transferase increase (2.3%), COVID-19 pneumonia (1.2%), cholangitis (1.2%), and fatigue (1.2%). No deaths resulted from AEs. Conclusions: In patients with chemotherapy-refractory HER2+ mCRC, tucatinib in combination with trastuzumab was well tolerated with clinically meaningful antitumor activity including durable responses and a median overall survival of 2 years. Tucatinib in combination with trastuzumab has the potential to become a new standard of care for patients with HER2+ mCRC. Clinical trial identification: NCT03043313. Editorial acknowledgement: The authors thank Joseph Giaconia of MMS Holdings, Michigan, USA for providing medical writing support/editorial support, which was funded by Seagen Inc., Bothell, WA, USA in accordance with Good Publication Practice (GPP3) guidelines. Legal entity responsible for the study: Seagen Inc. Funding: Seagen Inc. Disclosures: J. Strickler: Advisory / Consultancy: Seagen, Bayer, Pfizer;Research grant / Funding (institution): Amgen, Roche/Genentech, Seagen. A. Cercek: Advisory / Consultancy: Bayer, Merck, Seagen;Research grant / Funding (institution): Seagen, GSK, Rgenix. T. André: Honoraria (self : Amgen, Astra-Zeneca, Bristol-Myers Squibb, Gritstone Oncology, GlaxoSmithKline, Haliodx, Kaleido Biosciences, Merck & Co., Inc., Pierre Fabre, Sanofi, Servier, Merck & Co., Inc, Servier;Advisory / Consultancy: Astellas Pharma, BMS, Gritstone Oncology, Transgène, Roche/Ventana, Seagen, Merck & Co., Inc, Servier;Research grant / Funding (institution): BMS, Seagen, GSK;Travel / Accommodation / Expenses: BMS, Merck & Co., Inc. K. Ng: Advisory / Consultancy: Seattle Genetics, Bicara Therapeutics, GlaxoSmithKline;Research grant / Funding (institution): Pharmavite, Evergrande Group, Janssen. E. Van Cutsem: Advisory / Consultancy: AbbVie, Array, Astellas, AstraZeneca, Bayer, Beigene, Biocartis, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Daiichi, Halozyme, GSK, Helsinn, Incyte, Ipsen, Janssen Research, Lilly, Merck Sharp & Dohme, Merck KGaA, Mirati, Novartis, Pierre Fabre, Roche, Seattle Genetics, Servier, Sirtex, Terumo, Taiho, TRIGR, Zymeworks;Research grant / Funding (institution): Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Ipsen, Lilly, Merck Sharp & Dohme, Merck KGaA, Novartis, Roche, Servier. C. Wu: Research grant / Funding (institution): Seagen. A. Paulson: Research grant / Funding (institution): Seattle Genetics. J. Hubbard: Research grant / Funding (institution): Seattle Genetics. H. Lenz: Honoraria (self): BMS, Bayer, Roche;Advisory / Consultancy: Bayer, Merck, Roche;Travel / Accommodation / Expenses: BMS, Bayer, Merck KG;Shareholder / Stockholder / Stock options: Fulgent. M. Stecher: Full / Part-time employment: SeaGen. W. Feng: Full / Part-time employment: Seagen. T. Bekaii-Saab: Honoraria (self): Royalties: Uptodate;Advisory / Consultancy: Consulting (to institution): Ipsen, Arcus, Pfizer, Seattle Genetics, Bayer, Genentech, Incyte, Eisai and Merck., Consulting (to self): Stemline, AbbVie, Boehringer Ingelheim, Janssen, Daichii Sankyo, Natera, TreosBio, Celularity, Exact Science, Sobi, Beigene, Kanaph, Astra Zeneca, Deciphera, MJH Life Sciences, Aptitude Health, Illumina and Foundation Medicine, IDMC/DSMB: Fibrogen, Suzhou Kintor, Astra Zeneca, Exelixis, Merck/Eisai, PanCan and 1Globe;Research grant / Funding (institution): Agios, Arys, Arcus, Atreca, Boston Biomedical, Bayer, Eisai, Celgene, Lilly, Ipsen, Clovis, Seattle Genetics, Genentech, Novartis, Mirati, Merus, Abgenomics, Incyte, Pfizer, BMS.;Licensing / Royalties: WO/2018/183488: HUMAN PD1 PEPTIDE VACCINES AND USES THEREOF – Licensed to Imugene, WO/2019/055687: METHODS AND COMPOSITIONS FOR THE TREATMENT OF CANCER CACHEXIA – Licensed to Recursion. All other authors have declared no conflicts of interest.

Rapid response infrastructure for pandemic preparedness in a tertiary care hospital: lessons learned from the COVID-19 outbreak in Cologne, Germany, February to March 2020

The coronavirus disease (COVID-19) pandemic has caused tremendous pressure on hospital infrastructures such as emergency rooms (ER) and outpatient departments. To avoid malfunctioning of critical services because of large numbers of potentially infected patients seeking consultation, we established a COVID-19 rapid response infrastructure (CRRI), which instantly restored ER functionality. The CRRI was also used for testing of hospital personnel, provided epidemiological data and was a highly effective response to increasing numbers of suspected COVID-19 cases.