The impact of cancer metastases on COVID-19 outcomes: A COVID-19 and Cancer Consortium registry-based retrospective cohort study.

BACKGROUND: COVID-19 can have a particularly detrimental effect on patients with cancer, but no studies to date have examined if the presence, or site, of metastatic cancer is related to COVID-19 outcomes. METHODS: Using the COVID-19 and Cancer Consortium (CCC19) registry, the authors identified 10,065 patients with COVID-19 and cancer (2325 with and 7740 without metastasis at the time of COVID-19 diagnosis). The primary ordinal outcome was COVID-19 severity: not hospitalized, hospitalized but did not receive supplemental O2 , hospitalized and received supplemental O2 , admitted to an intensive care unit, received mechanical ventilation, or died from any cause. The authors used ordinal logistic regression models to compare COVID-19 severity by presence and specific site of metastatic cancer. They used logistic regression models to assess 30-day all-cause mortality. RESULTS: Compared to patients without metastasis, patients with metastases have increased hospitalization rates (59% vs. 49%) and higher 30 day mortality (18% vs. 9%). Patients with metastasis to bone, lung, liver, lymph nodes, and brain have significantly higher COVID-19 severity (adjusted odds ratios [ORs], 1.38, 1.59, 1.38, 1.00, and 2.21) compared to patients without metastases at those sites. Patients with metastasis to the lung have significantly higher odds of 30-day mortality (adjusted OR, 1.53; 95% confidence interval, 1.17-2.00) when adjusting for COVID-19 severity. CONCLUSIONS: Patients with metastatic cancer, especially with metastasis to the brain, are more likely to have severe outcomes after COVID-19 whereas patients with metastasis to the lung, compared to patients with cancer metastasis to other sites, have the highest 30-day mortality after COVID-19.

Combining Panitumumab With Anti-PD-1 Antibody in Cutaneous Squamous Cell Carcinoma of the Head and Neck After Inadequate Response to Anti-PD-1 Antibody Alone.

Anti-epidermal growth factor receptor (EGFR) antibodies and anti-programmed cell death 1 protein (PD-1) antibodies have been used separately to treat metastatic cutaneous squamous cell carcinoma (cSCC). While two anti-EGFR antibodies have similar clinical activity, cetuximab is administered weekly, whereas panitumumab is administered every two weeks. This report details findings using panitumumab in combination with anti-PD-1 antibody in patients with relapsed refractory cSCC. Three consecutive patients with poor performance status and rapidly progressive recurrent cutaneous squamous cell carcinoma (cSCC) of the face or scalp signed informed consent to receive an anti-PD-1 antibody with the option to add panitumumab were there inadequate response. After 2, 5, and 7 cycles of anti-PD-1 antibody treatment, respectively, panitumumab was added and the combination was continued for 27, 7, and 5 cycles, respectively. Fatigue, rash, and hypomagnesemia were reported, consistent with expectations for either agent alone. All three patients achieved durable complete response. The favorable clinical outcomes support further evaluation of the combination of anti-PD1 and anti-EGFR antibodies to control refractory cSCC of the face or scalp. J Drugs Dermatol. 2021;20(8):901-904. doi:10.36849/JDD.6175.

Assessing the Value of Next-Generation Sequencing Tests in a Dynamic Environment.

Next-generation sequencing (NGS)-based technology has lowered the cost of cancer testing for genomic alterations and is now commercially available from a growing number of diagnostic laboratories. However, laboratories vary in the methodologies underlying their tests, the types and numbers of genomic alterations covered by the test, and the clinical annotation of the sequencing findings. Determining the value of NGS tests is dependent on whether it is used to support clinical trials or as a part of routine clinical care at a time when both the investigational drug pipeline and the list of U.S. Food and Drug Administration-approved or Compendium-listed therapeutics is in a high state of flux. Reimbursement policy for NGS testing by the Centers for Medicare & Medicaid is evolving as the value of NGS testing becomes more clearly defined for specific clinical situations. Patient care and clinical decisions-making are dependent on the oncologist's knowledge of when NGS testing has value. Here, we review principles and practice for NGS testing in this dynamic confluence of technology, cancer biology, and health care policy.

Synergistic drug combinations from electronic health records and gene expression.

OBJECTIVE: Using electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding. METHOD: We applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis. RESULTS: From EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence. CONCLUSIONS: This is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing.

Challenges in Measuring Cost and Value in Oncology: Making It Personal.

Oncology patients often find themselves facing an incurable disease with limited treatment options and increasing patient fragility. The importance of patient preferences and values increases in shared decision making especially when the cost of cancer care is continuing its steep rise. As our understanding of cancer systems biology increases, we are justifiably optimistic about therapeutic improvements but recognize that this has complicated the traditional Food and Drug Administration approval of drug indications based on organ-specific cancer for a particular drug. Dynamic and agile clinical guidelines that reflect a rapidly changing knowledge base for decision-making support are needed. The American Society of Clinical Oncology (ASCO) has been working on three initiatives to tackle these complex issues. The first initiative is ASCO's collaboration with other international organizations to create a framework to assess drugs for the World Health Organization's Essential Medicines List, including nongenerics. The second initiative aims to define clinically meaningful outcomes as precision medicine expands the definition of cancers, leading to increased demand for the use of targeted drugs as single agents or in combination. The third initiative is ASCO's value framework, published in 2015, focusing on patient-physician shared decision making. The framework incorporates three parameters: 1) the meaningfulness of the clinical benefit, 2) the toxicity of the treatment, and 3) the patient's financial out-of-pocket cost. ASCO is concerned about the rising cost of cancer care when the clinical complexity and the pace of change in oncology are accelerating, and it is committed to help improve patient outcomes and value in cancer care as well as to engage the broader health care community in a process of collaborative improvement.

Use of Gene Expression Profiling and Chemotherapy in Early-Stage Breast Cancer: A Study of Linked Electronic Medical Records, Cancer Registry Data, and Genomic Data Across Two Health Care Systems.

PURPOSE: The 21-gene recurrence score (RS) identifies patients with breast cancer who derive little benefit from chemotherapy; it may reduce unwarranted variability in the use of chemotherapy. We tested whether the use of RS seems to guide chemotherapy receipt across different cancer care settings. METHODS: We developed a retrospective cohort of patients with breast cancer by using electronic medical record data from Stanford University (hereafter University) and Palo Alto Medical Foundation (hereafter Community) linked with demographic and staging data from the California Cancer Registry and RS results from the testing laboratory (Genomic Health Inc., Redwood City, CA). Multivariable analysis was performed to identify predictors of RS and chemotherapy use. RESULTS: In all, 10,125 patients with breast cancer were diagnosed in the University or Community systems from 2005 to 2011; 2,418 (23.9%) met RS guidelines criteria, of whom 15.6% received RS. RS was less often used for patients with involved lymph nodes, higher tumor grade, and age < 40 or ≥ 65 years. Among RS recipients, chemotherapy receipt was associated with a higher score (intermediate v low: odds ratio, 3.66; 95% CI, 1.94 to 6.91). A total of 293 patients (10.6%) received care in both health care systems (hereafter dual use); although receipt of RS was associated with dual use (v University: odds ratio, 1.73; 95% CI, 1.18 to 2.55), there was no difference in use of chemotherapy after RS by health care setting. CONCLUSION: Although there was greater use of RS for patients who sought care in more than one health care setting, use of chemotherapy followed RS guidance in University and Community health care systems. These results suggest that precision medicine may help optimize cancer treatment across health care settings.

Breast cancer treatment across health care systems: linking electronic medical records and state registry data to enable outcomes research.

BACKGROUND: Understanding of cancer outcomes is limited by data fragmentation. In the current study, the authors analyzed the information yielded by integrating breast cancer data from 3 sources: electronic medical records (EMRs) from 2 health care systems and the state registry. METHODS: Diagnostic test and treatment data were extracted from the EMRs of all patients with breast cancer treated between 2000 and 2010 in 2 independent California institutions: a community-based practice (Palo Alto Medical Foundation; "Community") and an academic medical center (Stanford University; "University"). The authors incorporated records from the population-based California Cancer Registry and then linked EMR-California Cancer Registry data sets of Community and University patients. RESULTS: The authors initially identified 8210 University patients and 5770 Community patients; linked data sets revealed a 16% patient overlap, yielding 12,109 unique patients. The percentage of all Community patients, but not University patients, treated at both institutions increased with worsening cancer prognostic factors. Before linking the data sets, Community patients appeared to receive less intervention than University patients (mastectomy: 37.6% vs 43.2%; chemotherapy: 35% vs 41.7%; magnetic resonance imaging: 10% vs 29.3%; and genetic testing: 2.5% vs 9.2%). Linked Community and University data sets revealed that patients treated at both institutions received substantially more interventions (mastectomy: 55.8%; chemotherapy: 47.2%; magnetic resonance imaging: 38.9%; and genetic testing: 10.9% [P < .001 for each 3-way institutional comparison]). CONCLUSIONS: Data linkage identified 16% of patients who were treated in 2 health care systems and who, despite comparable prognostic factors, received far more intensive treatment than others. By integrating complementary data from EMRs and population-based registries, a more comprehensive understanding of breast cancer care and factors that drive treatment use was obtained.

The ethics of health information technology in oncology: emerging isssues from both local and global perspectives.

Health information technology (HIT) is ever-increasing in complexity and has incrementally become a fundamental part of our everyday clinical lives. As HIT becomes more complex and commonplace, so do the questions it raises about stewardship and usage of data, along with the ethics of these applications. With the development of rapid-learning systems, such as ASCO's CancerLinQ, careful thought about the ethics and applications of these technologies is necessary. This article uses the principles-based framework of modern bioethics to examine evolving ethical issues that arise in the context of HIT and also discusses HIT's application in reducing cancer care disparities in the developing world. We recognize that this topic is quite broad, so here we provide an overview of the issues, rather than any definitive conclusions about a particular "correct path." Our hope is to stimulate discussion about this important topic, which will increasingly need to be addressed in the oncology community.