ABSTRACT
Purpose: The SARS-CoV-2 pandemic was declared a global public health emergency. Determinants of mortality in the general population are now clear, but specific data on patients with breast cancer (BC) remain limited, particularly in developing nations. Material(s) and Method(s): We conducted a longitudinal, multicenter cohort study in patients with BC and confirmed SARS-CoV-2 infection. The primary end point was the proportion of patients on treatment for severe SARS-CoV-2 infection (defined as need for hospitalization) or early death (within 30 days of diagnosis). Data were evaluated sequentially in the following way: i) univariate Fisher's exact test;ii) multivariable logistic regression analysis;and iii) multivariable logistic regression. In items i and ii only those with P< 0.1 are considered significant and in stage iii only those with p< 0.05 were the final significant variables. We divided patients' data into three major variable domains: a) signs and symptoms;b) comorbidities;and c) tumor and treatment characteristics;in item ii each variable domain was tested separately, finally, in item iii the significant variables of all domains were tested together and we called it the integrative step. Result(s): From April 2020 to June 2021, 413 patients with BC and COVID-19 were retrospectively registered, of which 288 (70%) had an identified molecular subtype and 273 (66%) had stage information. Most patients were on active systemic therapy or radiotherapy (73.2%), most of them in the curative setting (69.5%). The overall rate of severe SARS-CoV-2 was 19.7% (95% CI, 15.3-25.1). In the integrative multivariate analysis, factors associated with severe infection were metastatic setting, chronic pain, acute dyspnea, and cardiovascular comorbidities. Recursive partitioning modeling used acute dyspnea, metastatic setting, and cardiovascular comorbidities to predict nonprogression to severe infection, yielding a negative predictive value of 84.9% (95% CI, 78.9%-88.3%). Conclusion(s): The rate of severe COVID-19 in patients with BC is influenced by prognostic factors that partially overlap with those reported in the general population. High-risk patients should be considered candidates to active preventive measures to reduce the risk of infection, close monitoring in the case of exposure or SARS-CoV-2 -related symptoms and prophylactic treatment once infected.
ABSTRACT
Background: Despite advances in the treatment of mCRC combining chemotherapy regimens with biologics, most patients (pts) still progress within 11 months of receiving 1L chemotherapy. Addition of novel therapies to the standard of care (SoC) to improve antitumor activity is urgently needed. The randomized part 2 of COLUMBIA-1 (NCT04068610) evaluated the safety and efficacy of combining SoC (bevacizumab [BEV] + FOLFOX) with the PD-L1 inhibitor durvalumab (D) and the anti-CD73 monoclonal antibody oleclumab (O). Method(s): Pts with previously untreated, MSS-mCRC and ECOG PS <=1 received either SoC alone or SoC + D (1500 mg, Q4W) + O (3000 mg Q2W x4 then Q4W) in the experimental arm (EXP). The primary endpoint was objective response rate (ORR) per investigator assessed RECIST v1.1. Result(s): As of 10 Dec 2021, 52 pts were enrolled, of whom 51 were response evaluable. The confirmed ORR with SoC was 44.0% (95% confidence interval [CI], 24.4-65.1%) compared to 61.5% (95% CI, 40.6-79.8%) in the EXP arm. Median OS was not reached (SoC) vs 19.1 mos (EXP);median PFS was 11.1 mos (SoC) vs 10.9 mos (EXP;Table). Grade >=3 treatment emergent adverse events (TEAEs) occurred in 76.9% of pts in SoC and 65.4% EXP. Fatal TEAEs (all unrelated) were observed in 3 pts in the EXP arm: 1 with sepsis and 2 with intestinal perforation. One pt with intestinal perforation deemed related to BEV experienced fatal peritonitis. In the SoC arm, there was a single fatal COVID-19 TEAE. The most frequent treatment-related AEs in the EXP arm were diarrhea (38.5%), peripheral sensory neuropathy (38.5%) and fatigue (26.9%). There was no identified association between CD73 expression and clinical benefit. Conclusion(s): Addition of D + O to FOLFOX + BEV SoC showed a moderate response increase without PFS benefit vs SoC alone. Safety was consistent with known safety profiles. [Formula presented] Clinical trial identification: NCT04068610. Editorial acknowledgement: Editing support for this , under the direction of the authors, was provided by Catherine Crookes of Ashfield MedComms (Macclesfield, UK), an Inizio company, and was funded by AstraZeneca. Legal entity responsible for the study: AstraZeneca. Funding(s): AstraZeneca. Disclosure: N.H. Segal: Financial Interests, Personal, Advisory Board: Immunocore, PsiOxus, Roche/Genentech, BI, Revitope, ABL Bio, Novartis, GSK, AstraZeneca, Numab;Financial Interests, Personal, Research Grant: Regeneron, Immunocore, PureTech, AstraZeneca, BMS, Merck, Pfizer, Roche/Genentech. J. Tie: Financial Interests, Personal, Invited Speaker, Honorarium: Novartis, Amgen, Merck Serono, Merck Sharp and Dohme, Pierre Fabre;Financial Interests, Personal, Advisory Board: Haystack Oncology, Amgen, Novartis, AstraZeneca, Merck Serono, Merck Sharp and Dohme, Pierre Fabre, BMS;Non-Financial Interests, Personal, Principal Investigator: AstraZeneca, Pfizer, Daiichi Sankyo, Novartis. S. Kopetz: Financial Interests, Personal, Ownership Interest: MolecularMatch, Lutris, Iylon;Financial Interests, Personal, Research Grant: Sanofi, Biocartis, Guardant Health, Array BioPharma, Genentech/Roche, EMD Serono, AstraZeneca, Novartis, Amgen, Lilly, Daiichi Sankyo;Financial Interests, Personal, Other: Genetech, EMD Serono, Merck, Holy Stone, Novartis, Lilly, BI, Boston Biomedical, AstraZeneca, Bayer Health, Pierre Fabre, Redx Pharma, Ipsen, Daiichi Sankyo, Natera, HalioDx, Lutris, Jacobio, Pfizer, Repare Therapeutics, Inivata, GSK, Jazz Pharmaceuticals, Iylon, Xilis, AbbVie, Amal Therapeutics, Gilead, Mirati, Flame Biosciences, Servier, Carina Biotechnology, Bicara Therapeutics, Endeavor BioMedicines, Numab Pharma, Johnson and Johnson/Janssen. M.P. Ducreux: Financial Interests, Personal, Invited Speaker: Roche, Beigene, MSD, Servier, Pierre Fabre, Amgen;Financial Interests, Personal, Advisory Board: Terumo, Roche, Merck Serono, Bayer, Daiichi Sankyo, Sotio;Financial Interests, Institutional, Research Grant: Keocyt, Roche, Bayer. E. Chen: Financial Interests, Personal, Advisory Board: AstraZeneca;Financial Interests, Personal, Princip l Investigator: AstraZeneca. R. Dienstmann: Financial Interests, Personal, Speaker's Bureau: Roche, BI, Ipsen, Amgen, Servier, Sanofi, Libbs, Merck Sharp and Dohme, Lilly, AstraZeneca;Financial Interests, Personal, Advisory Board: Roche, BI;Financial Interests, Personal, Research Grant: Merck, Pierre Fabre. A. Hollebecque: Financial Interests, Personal, Invited Speaker: Servier, Incyte, EISAI;Financial Interests, Personal, Advisory Board: Basilea, Tahio, Relay Theraeutics, QED Therapeutics, Debiopharm;Financial Interests, Institutional, Funding: Incyte;Financial Interests, Institutional, Research Grant: AstraZeneca;Non-Financial Interests, Personal, Principal Investigator, M19-345: AbbVie;Non-Financial Interests, Personal, Principal Investigator, CO42216: Roche;Non-Financial Interests, Personal, Principal Investigator, MCLA-158: Merus;Non-Financial Interests, Personal, Principal Investigator, SGNB6A: Seattle Genetics;Non-Financial Interests, Personal, Principal Investigator, TAS-120-202: Tahio;Non-Financial Interests, Personal, Principal Investigator, Krystal-10: Mirati;Non-Financial Interests, Personal, Principal Investigator, ADP-0033: Adaptimmune;Non-Financial Interests, Personal, Principal Investigator, ACT16902: Sanofi;Non-Financial Interests, Personal, Principal Investigator, C4201002: Pfizer;Non-Financial Interests, Personal, Principal Investigator, RLY-4008: Relay Therapeutics;Non-Financial Interests, Personal, Principal Investigator, CC-90011: Celgene/BMS;Non-Financial Interests, Personal, Principal Investigator, Loxo-IDH: Loxo/Lilly;Non-Financial Interests, Personal, Principal Investigator: AstraZeneca. M. Reilley: Financial Interests, Personal, Advisory Board: BMS, Helsinn, ZielBio. M.E. Elez Fernandez: Financial Interests, Personal, Invited Speaker: Novartis, Organon;Financial Interests, Personal, Advisory Board: Amgen, Bayer, F. Hoffman La Roche, Merck Serono, MSD, Pierre Fabre, Sanofi, Servier;Financial Interests, Institutional, Funding: Amgen, Array Biopharma, AstraZeneca, BeiGene, BI, BMS, Celgene, Debiopharm International SA, F. Hoffman La Roche, Genentech, HalioDX SAS, Hutchinson MediPharma International, Janssen-Cilag SA, Menarini, Merck ealth KgaA, MSD, Merus NV, Mirati, Novartis Farmaceutica SA, Pfizer, PharmaMar, Sanofi Aventis Recherche & Developpement, Servier, Taiho Pharma;Financial Interests, Personal, Other, ASCO Scientific Program Committee: Developmental Therapeutics - Immunotherapy: ASCO;Financial Interests, Personal, Other, Speaker of the ESMO Academy: ESMO;Financial Interests, Personal, Other, Coordinator of the SEOM +MIR Section of Residents and Young Assistants: SEOM;Financial Interests, Personal, Other, Travel, accommodations, expenses: Amgen, Array BioPharma, BMS, Merck Serono, Roche, Sanofi, Servier. J. Cosaert: Financial Interests, Personal, Full or part-time Employment: AstraZeneca;Financial Interests, Personal, Stocks/Shares: AstraZeneca;Financial Interests, Personal, Member: AstraZeneca. J. Cain: Financial Interests, Personal, Full or part-time Employment: AstraZeneca. M. Hernandez: Financial Interests, Personal, Full or part-time Employment: AstraZeneca;Financial Interests, Personal, Stocks/Shares: AstraZeneca. N. Hewson: Financial Interests, Personal, Full or part-time Employment: AstraZeneca. Z.A. Cooper: Financial Interests, Personal, Full or part-time Employment: AstraZeneca;Financial Interests, Personal, Stocks/Shares: AstraZeneca. M. Dressman: Financial Interests, Personal, Full or part-time Employment: AstraZeneca;Financial Interests, Personal, Stocks/Shares: AstraZeneca. J. Tabernero: Financial Interests, Personal, Advisory Role: Array BioPharma, AstraZeneca, Bayer, BI, Chugai, Daiichi Sankyo, F. Hoffman-La Roche Ltd, Genentech, HalioDX SAS, Hutchison MediPharma International, Ikena Oncology, Inspirna Inc, IQVIA, Lilly, Menarini, Merck Serono, Merus, MSD, Mirati, Neophore, Novartis, Ona Therapeutics, Orion Biotechnology, Peptomyc, Pfizer, Pierre Fabre, Samsung Bioepis, Sanofi, Scandio Oncology, Scorpion Therapeutics, Seattle Genetics, Servier, Sotio Biotech, Taiho, Tessa Therapeutics, TheraMyc;Financial Interests, Personal, Stocks/Shares: Oniria Therapeutics;Financial Interests, Personal, Other, educational collaboration: Imedex/HMP, Medscape Education, MJH Life Sciences, PeerView Institute for Medical Education, Physicians Education Resource (PER). Copyright © 2022 European Society for Medical Oncology
ABSTRACT
Background: As a reaction to the COVID-19 pandemic, a nation-wide lockdown was enforced in Brazil in March 2020, cancer care was impacted, and cancer screening reduced. Therefore, an increase in cancer diagnoses at more advanced stages was expected. In this study, we extracted data from our nationwide real-world database to evaluate the impact of the COVID-19 pandemic on the stage at diagnosis of breast cancer (BC) cases. Methods: We explored curated electronic medical record data of female patients, over 18 years of age, diagnosed with BC and with established disease stage based on the AJCC 8th edition, who started treatment or follow-up in the Oncoclínicas (OC) between Jan 1, 2018, and Dec 31, 2021. The primary objective was to compare stage distribution at first visit during COVID- 19 pandemic (2020-2021) with a historical control cohort from a period prior to the pandemic (2018- 2019). We investigated stage distribution according to age at diagnosis and tumor ER/HER2 subtype in univariate models. Associations were considered significant if they had a minimum significance (P < 0.1 in Chi-square test). The historical numbers of patients with BC at OC make it possible to identify differences in the prevalence of stages in the order of 5% comparing pre and post pandemic periods with a statistical power greater than 80%. Results: We collected data for 11,752 patients with initial diagnosis of BC, with 6,492 patients belonging to the pandemic (2020-2021) and 5,260 patients to the pre-pandemic period (2018-2019). For both ER+/ HER2- and HER2+ tumors, there was a lower percentage of patients with early-stage (defined as stage I-II) in the years 2020-2021 vs 2018-2019 and a considerable increase in advanced-stage disease (defined as stage IV). For triple negative BC (TNBC), there was a significant higher percentage of patients with advanced-stage disease in the pandemic vs pre-pandemic period (table 1). Age over 50 years was associated with a greater risk of advanced stage at diagnosis after the onset of the pandemic, with an absolute increase of 7% (P twosided <0.01). Conclusions: We observed a substantial increase in cases of advanced-stage BC in OC institutions as a result of delays in BC diagnoses due to the COVID-19 pandemic. The impact appeared greater in older adults, potentially because of stricter confinement in this group.
ABSTRACT
Background: The COVID-19 pandemic remains a public health emergency of global concern, with higher mortality rates in cancer patients as compared to the general population. However, early mortality of COVID19 in cancer patients has not been compared to historical real-world data from oncology population in pre-pandemic times. Methods: Longitudinal multicenter cohort study of patients with cancer and confirmed COVID-19 from Oncoclínicas Group in Brazil from March to December 2020. The primary endpoint was 30-day mortality after isolation of the SARS-CoV-2 by RT-PCR. As historical control, we selected patients from Oncoclínicas Data Lake treated before December 2019 and propensity score-matched to COVID-19 cases (3:1) based on the following clinical characteristics: age, gender, tumor type, disease setting (curative or palliative), time from diagnosis of cancer (or metastatic disease) to COVID-19 infection. Results: In total, 533 cancer patients with COVID-19 were prospectively registered in the database, with median age 60 years, 67% females, most frequent tumor types breast (34%), hematological (16%), gastrointestinal (15%), genitourinary (12%) and respiratory tract malignancies (10%). Most patients were on active systemic therapy or radiotherapy (84%), largely for advanced or metastatic disease (55%). In the overall population, early death rate was 15%, which was numerically higher than the Brazilian general population with COVID-19 diagnosis in 2020 (2.5%). We were able to match 442 cancer patients with COVID-19 to 1,187 controls with cancer from pre-pandemic times. The 30-day mortality rate was 12.4% in COVID-19 cases as compared to 5.4% in pre-pandemic controls with cancer (Odds Ratio 2.49, 95%CI 1.67 - 3.70;P value < 0.01, Power 97.5%). COVID-19 cancer patients had significantly higher death events than historical controls (Hazard Ratio 2.18, 95%CI 1.52 - 3.12;P value < 0.01, Power 99.7%), particularly from 20 to 30 days after diagnosis of the infection. Conclusions: Cancer patients with COVID-19 have an excess mortality 30 days after the infection when compared to matched cancer population from pre-pandemic times and the general population with COVID-19, reinforcing the need for priority vaccination in public health strategies. Legal entity responsible for the study: Oncoclínicas Group. Funding: Amgen. Disclosure: All authors have declared no conflicts of interest.
ABSTRACT
Background: COVID-19 is a challenge for clinical decision-making in cancer patients and the allocation of healthcare resources. An accurate prognosis prediction to effectively triage patients is needed, especially in the community oncology practice. Methods:Nationwide cohort from Oncoclínicas Brazil was used to validate previously developed multivariable logistic regression (mLR) model (Ferrari et al, JCO GO 2021) and to construct a machine learning Random Forest (RF) algorithm as predictor of 30-day mortality after SARS-CoV-2 detection by RT-PCR in cancer patients diagnosed in an outpatient setting. To find the most important baseline clinical determinants of early COVID19-related death via Gini index, a RF with 100,000 trees was trained in 75% of the dataset, and the performance was assessed in the remaining 25%. We then compared the accuracy of different models in terms of sensitivity, specificity and area under the receiver operating characteristics curves (AUC). Results:From March to December 2020, 533 patients with COVID-19 were prospectively registered in the database. Median age was 60 years (19-93) and 67% were female. Most frequent cancers were breast in 34%, hematological in 16%, and gastrointestinal in 15%. Comorbidities were common (52%), as was current/former smoking history (17%). Most patients were on active systemic therapy or radiotherapy (84%) in the advanced or metastatic disease setting (55%). The overall mortality rate was 15% (CI95% 12%-18%). We validated the original mLR model trained in the first 198 patients: management in a noncurative setting (odds ratio [OR] 3.7), age ≥ 60 years (OR 2.3), and current/former smoking (OR 1.9) were significant predictors of death in the expanded cohort. Presence of comorbidities (OR 1.9) also defined poor outcome in the updated mLR model, which yielded low sensitivity (74%), specificity (68%) and AUC (0.78). With RF modeling, the most significant predictors of 30-day death after COVID-19 (in decreasing order) were older age, treatment of advanced or metastatic disease, tumor type (respiratory tract, brain and unknown primary cancers had higher mortality), COVID-related symptom burden at baseline evaluation and treatment regimen (immunotherapy combinations had higher mortality). The RF model demonstrated high sensitivity (89%), specificity (88%) and AUC (0.96). Conclusions:The results highlight the possibility that machine learning algorithms are able to predict early mortality after COVID-19 in cancer patients with high accuracy. The proposed prediction model may be helpful in the prompt identification of high-risk patients based on clinical features alone, without having to wait for the results of additional tests such as laboratory or radiologic studies. It can also help prioritize medical resources and redefine vaccination strategies. A web-based mortality risk calculator will be created for clinical decision support.
ABSTRACT
BACKGROUND: The COVID-19 pandemic has impacted all aspects of modern-day oncology, including how stakeholders communicate through social media. We surveyed oncology stakeholders in order to assess their attitudes pertaining to social media and how it has been affected during the pandemic. MATERIALS AND METHODS: A 40-item survey was distributed to stakeholders from 8 July to 22 July 2020 and was promoted through the European Society for Medical Oncology (ESMO) and the OncoAlert Network. RESULTS: One thousand and seventy-six physicians and stakeholders took part in the survey. In total, 57.3% of respondents were medical oncologists, 50.6% aged <40 years, 50.8% of female gender and mostly practicing in Europe (51.5%). More than 90% of respondents considered social media a useful tool for distributing scientific information and for education. Most used social media to stay up to date on cancer care in general (62.5%) and cancer care during COVID-19 (61%) given the constant flow of information. Respondents also used social media to interact with other oncologists (78.8%) and with patients (34.4%). Overall, 61.1% of respondents were satisfied with the role that social media was playing during the COVID-19 pandemic. On the other hand, 41.1% of respondents reported trouble in discriminating between credible and less credible information and 30% stated social networks were a source of stress. For this reason, one-third of respondents reduced its use during the COVID-19 pandemic. Regarding meeting attendance, a total of 59.1% of responding physicians preferred in-person meetings to virtual ones, and 51.8% agreed that virtual meetings and social distancing could hamper effective collaboration. CONCLUSION: Social media has a useful role in supporting cancer care and professional engagement in oncology. Although one-third of respondents reported reduced use of social media due to stress during the COVID-19 pandemic, the majority found social media useful to keep up to date and were satisfied with the role social media was playing during the pandemic.