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Integrated Survival Estimates for Cancer Treatment Delay Among Adults With Cancer During the COVID-19 Pandemic.
Hartman, Holly E; Sun, Yilun; Devasia, Theresa P; Chase, Elizabeth C; Jairath, Neil K; Dess, Robert T; Jackson, William C; Morris, Emily; Li, Pin; Hochstedler, Kimberly A; Abbott, Madeline R; Kidwell, Kelley M; Walter, Vonn; Wang, Ming; Wang, Xi; Zaorsky, Nicholas G; Schipper, Matthew J; Spratt, Daniel E.
  • Hartman HE; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Sun Y; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Devasia TP; Department of Radiation Oncology, University of Michigan, Ann Arbor.
  • Chase EC; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Jairath NK; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Dess RT; Department of Radiation Oncology, University of Michigan, Ann Arbor.
  • Jackson WC; Department of Radiation Oncology, University of Michigan, Ann Arbor.
  • Morris E; Department of Radiation Oncology, University of Michigan, Ann Arbor.
  • Li P; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Hochstedler KA; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Abbott MR; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Kidwell KM; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Walter V; Department of Biostatistics, University of Michigan, Ann Arbor.
  • Wang M; Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pennsylvania.
  • Wang X; Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pennsylvania.
  • Zaorsky NG; Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State University College of Medicine, Hershey, Pennsylvania.
  • Schipper MJ; Department of Radiation Oncology, Penn State Cancer Institute, Hershey, Pennsylvania.
  • Spratt DE; Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania.
JAMA Oncol ; 6(12): 1881-1889, 2020 12 01.
Article in English | MEDLINE | ID: covidwho-893187
ABSTRACT
Importance Cancer treatment delay has been reported to variably impact cancer-specific survival and coronavirus disease 2019 (COVID-19)-specific mortality during the severe acute respiratory syndrome coronavirus 2 pandemic. During the pandemic, treatment delay is being recommended in a nonquantitative, nonobjective, and nonpersonalized manner, and this approach may be associated with suboptimal outcomes. Quantitative integration of cancer mortality estimates and data on the consequences of treatment delay is needed to aid treatment decisions and improve patient outcomes.

Objective:

To obtain quantitative integration of cancer-specific and COVID-19-specific mortality estimates that can be used to make optimal decisions for individual patients and optimize resource allocation. Design, Setting, and

Participants:

In this decision analytical model, age-specific and stage-specific estimates of overall survival pre-COVID-19 were adjusted by the probability of COVID-19 (individualized by county, treatment-specific variables, hospital exposure frequency, and COVID-19 infectivity estimates), COVID-19 mortality (individualized by age-specific, comorbidity-specific, and treatment-specific variables), and delay of cancer treatment (impact and duration). These model estimates were integrated into a web application (OncCOVID) to calculate estimates of the cumulative overall survival and restricted mean survival time of patients who received immediate vs delayed cancer treatment. Using currently available information about COVID-19, a susceptible-infected-recovered model that accounted for the increased risk among patients at health care treatment centers was developed. This model integrated the data on cancer mortality and the consequences of treatment delay to aid treatment decisions. Age-specific and cancer stage-specific estimates of overall survival pre-COVID-19 were extracted from the Surveillance, Epidemiology, and End Results database for 691 854 individuals with 25 cancer types who received cancer diagnoses in 2005 to 2006. Data from 5 436 896 individuals in the National Cancer Database were used to estimate the independent impact of treatment delay by cancer type and stage. In addition, data from 275 patients in a nested case-control study were used to estimate the COVID-19 mortality rate by age group and number of comorbidities. Data were analyzed from March 17 to May 21, 2020. Exposures COVID-19 and cancer. Main Outcomes and

Measures:

Estimates of restricted mean survival time after the receipt of immediate vs delayed cancer treatment.

Results:

At the time of the study, the OncCOVID web application allowed for the selection of up to 47 individualized variables to assess net survival for an individual patient with cancer. Substantial heterogeneity was found regarding the association between delayed cancer treatment and net survival among patients with a given cancer type and stage, and these 2 variables were insufficient to discriminate the net impact of immediate vs delayed treatment. Individualized overall survival estimates were associated with patient age, number of comorbidities, treatment received, and specific local community estimates of COVID-19 risk. Conclusions and Relevance This decision analytical modeling study found that the OncCOVID web-based application can quantitatively aid in the resource allocation of individualized treatment for patients with cancer during the COVID-19 global pandemic.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Outcome Assessment, Health Care / SEER Program / COVID-19 / Neoplasms Type of study: Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: JAMA Oncol Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Outcome Assessment, Health Care / SEER Program / COVID-19 / Neoplasms Type of study: Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: JAMA Oncol Year: 2020 Document Type: Article