Central Nervous System Disease in phase III studies for advanced HER2 Positive Breast Cancer: A Review

IMPORTANCE: The introduction of human epidermal growth factor receptor 2 (HER2) directed therapy has transformed the outcomes of patients with advanced breast cancer (BC). However, HER2 positive breast cancer has a predilection for the central nervous system (CNS) which is associated with significant morbidity and mortality. Understanding the intracranial activity of novel HER2 directed agents is key to developing treatments as well as possible preventative strategies for HER2-positive CNS disease. OBSERVATIONS: Using protocols and data from published phase III clinical trials for locally advanced/metastatic HER2-positive breast cancer since the licensing of single agent trastuzumab for advanced BC we review the central nervous system related aspects. This includes CNS related entry criteria, use of baseline and on study cross-sectional imaging of the CNS and protocol and non-protocol defined CNS end points and reported data. CONCLUSIONS: and Relevance: This review found heterogeneity between studies with regard to the entry criteria, use of CNS imaging and reported end points within the pivotal phase III studies. Based on these data, a standardisation of both entry criteria and end points with regard to the CNS should be developed and applied to future studies of HER2-positive advanced BC. Such an approach would enable the generation of comparable data and allow a meaningful analysis of different treatment approaches with regard to the CNS. This in turn would allow the development of the most optimal treatment approaches for HER2 positive CNS disease and ultimately the development of preventative strategies

Haematological malignancy and nosocomial transmission are associated with an increased risk of death from COVID-19: results of a multi-center UK cohort.

The COVID-19 pandemic has been a disruptive event for cancer patients, especially those with haematological malignancies (HM). They may experience a more severe clinical course due to impaired immune responses. This multi-center retrospective UK audit identified cancer patients who had SARS-CoV-2 infection between 1 March and 10 June 2020 and collected data pertaining to cancer history, COVID-19 presentation and outcomes. In total, 179 patients were identified with a median age of 72 (IQR 61, 81) and follow-up of 44 days (IQR 42, 45). Forty-one percent were female and the overall mortality was 37%. Twenty-nine percent had HM and of these, those treated with chemotherapy in the preceding 28 days to COVID-19 diagnosis had worse outcome compared with solid malignancy (SM): 62% versus 19% died [HR 8.33 (95% CI, 2.56-25), p p = 0.001). Patients with haematological malignancies and those who acquire nosocomial transmission are at increased risk of death. Therefore, there is an urgent need to reassess shielding advice, reinforce stringent infection control, and ensure regular patient and staff testing to prevent nosocomial transmission

Central nervous system disease in phase III studies for advanced HER2 positive breast cancer: A review

IMPORTANCE: The introduction of human epidermal growth factor receptor 2 (HER2) directed therapy has transformed the outcomes of patients with advanced breast cancer (BC). However, HER2 positive breast cancer has a predilection for the central nervous system (CNS) which is associated with significant morbidity and mortality. Understanding the intracranial activity of novel HER2 directed agents is key to developing treatments as well as possible preventative strategies for HER2-positive CNS disease. OBSERVATIONS: Using protocols and data from published phase III clinical trials for locally advanced/metastatic HER2-positive breast cancer since the licensing of single agent trastuzumab for advanced BC we review the central nervous system related aspects. This includes CNS related entry criteria, use of baseline and on study cross-sectional imaging of the CNS and protocol and non-protocol defined CNS end points and reported data. CONCLUSIONS: and Relevance: This review found heterogeneity between studies with regard to the entry criteria, use of CNS imaging and reported end points within the pivotal phase III studies. Based on these data, a standardisation of both entry criteria and end points with regard to the CNS should be developed and applied to future studies of HER2-positive advanced BC. Such an approach would enable the generation of comparable data and allow a meaningful analysis of different treatment approaches with regard to the CNS. This in turn would allow the development of the most optimal treatment approaches for HER2 positive CNS disease and ultimately the development of preventative strategies

Non-invasive cardiac stress studies may not offer significant benefit in pre-kidney transplant evaluation:A retrospective cohort study

BackgroundScreening with cardiac non-invasive stress studies (NISS) prior to listing for kidney transplantation can help in identifying treatable coronary disease and is considered an integral part of pre-kidney transplant evaluation. However, few studies assessed their effectiveness in all patients evaluated for transplantation in clinical practice. To evaluate the role of NISS in pre-kidney transplant evaluation we analyzed their impact prior to waitlisting in 1053 adult CKD-5 patients consecutively evaluated in Greater Manchester, UK during a 6-year period.Methods918 waitlisted patients were grouped based on presence or absence of Diabetes or Cardio-Vascular Disease (CVD): Group-1 (255 DM-/CVD-/NISS-), Group-2 (368 DM-/CVD-/NISS+) and Group-3 (295 with DM or CVD).ResultsGroup-2 patients had longer 'time-to-listing' (5.5months in Group-1 vs 6.9months in 'Normal-NISS' vs 9.9months in 'Abnormal-NISS', pConclusionsPre-kidney transplant evaluation with NISS influenced clinical management in 19 of 1053 (2%) patients. Screening with NISS added limited benefit but contributes to significant delays in listing and adding resource implications. Further studies are needed to assess clinical and cost effectiveness of NISS in pretransplant evaluation to optimize outcomes and resources

Establishment of CORONET: COVID-19 Risk in Oncology Evaluation Tool to Identify Cancer Patients at Low Versus High Risk of Severe Complications of COVID-19 Infection Upon Presentation to Hospital

Background: Patients with cancer are at increased risk of severe COVID-19, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET).Methods: Patients with active cancer (stage I-IV) and laboratory confirmed COVID-19 presenting to hospitals worldwide were included. Discharge (within 24hrs), admission (≥24hrs inpatient), oxygen requirement (O2) and death were combined in a 0-3 point severity scale. Association of features with outcome were investigated using Lasso regression and Random Forest (RF) combined with SHapley Additive exPlanations (SHAP). RF was further validated in 4 cohorts, split by geography. The CORONET model was then examined in the entire cohort to build an online CORONET decision-support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions.Findings: The dataset comprised 920 patients; median age 70 (range 5-99), 56% males, 44% females, 81% solid vs. 19% haematological cancers. In derivation, RF demonstrated superior performance over Lasso with lower mean squared error (0.801 vs. 0.807) and was selected for development. During validation, RF achieved mean AUROC 0.77, 0.80 and 0.75 for prediction of admission, O 2 and death, respectively. Using the entire cohort, CORONET cut-offs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died. SHAP explanations revealed National-Early-Warning-Score-2, C-reactive protein and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation.Interpretation: CORONET, a decision-support tool validated in healthcare systems worldwide can aid admission decisions and predict COVID-19 severity in patients with cancer.Funding Information: R. Lee and T. Robinson and J. Weaver are supported by the National Institute for Health Research as Clinical Lecturers. T. Bhogal is supported by the National Institute for Health Research as an academic clinical fellow. U. Khan is an MRC Clinical Training Fellow based at the University of Liverpool supported by the North West England Medical Research Council Fellowship Scheme in Clinical Pharmacology and Therapeutics, which is funded by the Medical Research Council (Award Ref. MR/N025989/1). The Liverpool Experimental Cancer Medicine Centre for providing infrastructure support (Grant Reference: C18616/A25153) and The Clatterbridge Cancer charity (North West Cancer Research). C. Dive is funded by CRUK Core funding to Manchester Institute (C5757/A27412) and is supported by the CRUK Manchester Centre Award (C5759/A25254), and by the NIHR Manchester Biomedical Research Centre. C. Zhou is funded by the CRUK Manchester Centre Award (C5759/A25254), J. Stevenson and P. Fitzpatrick are funded by the CRUK Accelerator Award (29374). This research was funded in part, by the Wellcome Trust [205228/Z/16/Z]. LT is also supported by the National Institute for Health Research Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections (NIHR200907) at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford. LT is based at University of Liverpool. MS is supported by a grant from the Ministry of Science and Higher Education of the Russian Federation for the state support for the creation and development of World Class Research Centers "Digital biodesign and personalized healthcare” N.075-15-2020-926.Declaration of Interests: R Lee research funding (institution) BMS and speaker fees Astrazeneca. A. Croitoru Consulting or Advisory Role: Lilly, Merck, Roche, Bayer, Novartis, Ipsen, Research Funding me and my hospital: Gilead Sciences, Pfizer, Canfite, NanoCarrier, Bristol-Myers Squibb, Merck, Amgen, Servier, Five Prime Therapeutics, Travel Accommodations: Pfizer, Genekor, and oz, Merck, Pfizer, Servier, Roche. O. Michielin reports personal fees from Bristol-Myers Squibb, personal fees from MSD, personal fees from Novartis, personal fees from Roche, personal fees from Amgen, personal fees from NeraCare GmbH, outside the submitted work. E. Romano institutional research grants from Amgen, Astra Zeneca, Bristol-Myers Squibb. G. Pentheroudakis advisory board for Amgen, Astra Zeneca, Bristol-Myers Squibb, Lilly, Merck, MSD, Roche, Abbvie, institutional research grants from Amgen, Astra Zeneca, Boehringer Ingelheim, Bristol Myers Squibb, Debbio, Enorasis, Genekor, Ipsen, Janssen, Lilly, Merck, MSD, Pfizer, Roche, Sanofi, Servier. Solange Peters reports consultation/advisory role: AbbVie, Amgen, AstraZeneca, Bayer, Beigene, Biocartis, Bio Invent, Blueprint Medicines, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, Elsevier, F. Hoffmann-La Roche/Genentech, Foundation Medicine, Illumina, Incyte, IQVIA, Janssen, Medscape, Merck Sharp and Dohme, Merck Serono, Merrimack, Mirati, Novartis, Pharma Mar, Phosplatin Therapeutics, Pfizer, Regeneron, Sanofi, Seattle Genetics, Takeda, Vaccibody, talk in a company’s organized public event: AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, e-cancer, Eli Lilly, F. Hoffmann-La Roche/Genentech, Illumina, Medscape, Merck Sharp and Dohme, Novartis, PER, Pfizer, Prime, RTP, Sanofi, Takeda, receipt of grants/research supports: (Sub)investigator in trials (institutional financial support for clinical trials) sponsored by Amgen, AstraZeneca, Biodesix, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, F. Hoffmann-La Roche/Genentech, GSK, Illumina, Lilly, Merck Sharp and Dohme, Merck Serono, Mirati, Novartis, and Pfizer, Phosplatin Therapeutics. M Rowe honoraria from Astellas Pharma, speaker fees MSD and Servier. C. Wilson consultancy and speaker fees Pfizer, Amgen, Novartis, A Armstrong conference fee Merck, spouse shares in Astrazeneca. T Robinson financial support to attend educational workshops from Amgen and Daiichi-Sankyo. C Dive, outside of this scope of work, has received research funding from AstraZeneca, Astex Pharmaceuticals, Bioven, Amgen, Carrick Therapeutics, Merck AG, Taiho Oncology, Clearbridge Biomedics, Angle PLC, Menarini Diagnostics, GSK, Bayer, Boehringer Ingelheim, Roche, BMS, Novartis, Celgene, Thermofisher. C Dive is on advisory boards for, and has received consultancy fees/honoraria from, AstraZeneca, Biocartis and Merck KGaA.No other authors have nothing to declare. Ethics Approval Statement: Approval (reference 20/WA/0269) was granted from the UK Research Ethics Committee for the study. Information regarding governance/regulatory approvals for each international cohort are available in the Supp. Methods

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves

SIMPLE SUMMARY: There have been huge improvements in both vaccination and the management of COVID-19 in patients with cancer. In addition, different variants may be associated with different presentations. Therefore, we examined whether indicators of the severity of COVID-19 in patients with cancer who present to hospital varied during different waves of the pandemic and we showed that these indicators remained predictive. We validated that the COVID-19 Risk in Oncology Evaluation Tool (CORONET), which predicts the severity of COVID-19 in cancer patients presenting to hospital, performed well in all waves. In addition, we examined patient outcomes and the factors that influence them and found that there was increased vaccination uptake and steroid use for patients requiring oxygen in later waves, which may be associated with improvements in outcome. ABSTRACT: Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital.

PurposePatients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET).MethodsPatients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort.ResultsThe model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation.ConclusionCORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer