Financial toxicity includes both objective financial burden (ie, costs) and subjective financial distress.^1,2 Costs of cancer care include: direct cost of care (cost sharing through higher deductibles, copayments, coinsurance, and even entire cost of care for uninsured patients) and indirect costs of care (lost productivity and cost of driving to and from appointments).^1,3 Patients with cancer have greater time-based costs than those without cancer (eg, time spent traveling back and forth to appointments and time spent receiving medical care).^4-6 Strategies are needed to reduce the direct and indirect costs of cancer care delivery.

Importance: While the health care community advocates broadly for climate change policy, medical professionals can look within care practices to assess their contribution to carbon dioxide (CO₂) emissions, and provide solutions wherever possible. Telemedicine can help in mitigating climate change by providing care from a distance.Objective: To assess the carbon savings achieved from telemedicine visits.Design, Setting, and Participants: This cross-sectional study of telemedicine visits was conducted at a single-institution National Cancer Institute (NCI)-designated comprehensive cancer center. Eligible patients were aged 18 years and above, completed telemedicine visits from April 1, 2020, to June 20, 2021, and had a Florida mailing address documented in their electronic medical record. Groups were divided between those within driving time of 60 minutes (1-way) to the cancer center vs those living beyond 60 minutes of drive time. Data were analyzed between April 2020 and June 2021.Main Outcomes and Measures: Carbon emission savings from telemedicine, measured in total and average per-visit savings.Results: A total 49 329 telemedicine visits with 23 228 patients were conducted from April 1, 2020, to June 30, 2021. A total 21 489 visits were for patients with driving time of 60 minutes or less (median [IQR] age, 62.0 [52.0-71.0] years; 12 334 [57.4%] female; 1685 [7.8%] Black, 1500 [7.0%] Hispanic, 16 010 [74.5%] non-Hispanic White), while 27 840 visits were for patients with driving time greater than 60 minutes (median [IQR] age, 67.0 [57.0-74.0] years; 14 372 [51.6%] female; 1056 [3.8%] Black, 1364 [5.0%] Hispanic, 22 457 [80.7%] non-Hispanic White). For patients living within a driving time of 60 minutes from the cancer center, 424 471 kg CO₂ emissions were saved (mean [SD] emissions savings, 19.8 [9.4] kg CO₂ per visit) due to telemedicine—equivalent to 91.5 passenger vehicles driven for 1 year. For patients whose driving distance was greater than 60 minutes, 2 744 248 kg CO₂ emissions were saved (mean emissions savings, 98.6 [54.8] kg CO₂ per visit)—equivalent to 591 passenger vehicles driven for 1 year.Conclusions and Relevance: Using a large data set, this cross-sectional analysis highlighted the carbon emissions savings due to telemedicine in oncology. This has important implications in reducing health care–related carbon footprint.

We hypothesized the combination of cetuximab and nivolumab would improve survival in recurrent and/or metastatic (R/M) HNSCC by providing synergy in cancer control and evaluated toxicities and efficacy of the combination. Effects of sequential administration of cetuximab and anti-Programmed Cell Death-1 checkpoint inhibitors (CPI) were also explored. Patients who failed at least one line of palliative treatment for incurable HNSCC were treated with cetuximab 500 mg/m² IV on Day (D)-14 as a lead-in followed by cetuximab 500 mg/m² IV and nivolumab 240 mg/m² IV on D1 and D15 every 28-D cycle. Electronic health record-derived real-world data (RWD) were used to explore sequential treatment effects of CPI and cetuximab. A total of 45 evaluable patients were analyzed, and 31/45 (69%) patients had prior exposure to either CPI or cetuximab. The only grade 4 treatment-related adverse event was cetuximab infusion reaction in one patient. The 1-year progression-free survival (PFS) and overall survival (OS) rates were 19% and 44%, respectively. Although patients with no prior CPI (23/45, 51%) showed a trend for more favorable PFS relative to patients with prior CPI (22/45, 49%), the improvement in the 1-year OS did not reach the statistical threshold. For evaluation of sequential CPI and cetuximab treatment effects, we selected RWD-cetuximab cohort with 173 patients and RWD-CPI cohort with 658 patients from 6862 R/M HNSCC. Our result suggested patients treated with RWD-cetuximab after RWD-CPI had worse OS compared to no prior RWD-CPI (HR 1.81, 95% CI 1.02–3.16). Our data suggest the combination of cetuximab and nivolumab is well tolerated. Optimal sequencing of cetuximab and CPI may have an impact in prognosis and requires further evaluation.

Background: Rapid implementation of telehealth for cancer care during COVID-19 required innovative and adaptive solutions among oncology health care providers and professionals (HPPs). Objective: The aim of this qualitative study was to explore oncology HPPs’ experiences with telehealth implementation during the COVID-19 pandemic. Methods: This study was conducted at Moffitt Cancer Center (Moffitt), an NCI (National Cancer Institute)-Designated Comprehensive Cancer Center. Prior to COVID-19, Moffitt piloted telehealth visits on a limited basis. After COVID-19, Moffitt rapidly expanded telehealth visits. Telehealth visits included real-time videoconferencing between HPPs and patients and virtual check-ins (ie, brief communication with an HPP by telephone only). We conducted semistructured interviews with 40 oncology HPPs who implemented telehealth during COVID-19. The interviews were recorded, transcribed verbatim, and analyzed for themes using Dedoose software (version 4.12). Results: Approximately half of the 40 participants were physicians (n=22, 55%), and one-quarter of the participants were advanced practice providers (n=10, 25%). Other participants included social workers (n=3, 8%), psychologists (n=2, 5%), dieticians (n=2, 5%), and a pharmacist (n=1, 3%). Five key themes were identified: (1) establishing and maintaining patient-HPP relationships, (2) coordinating care with other HPPs and informal caregivers, (3) adapting in-person assessments for telehealth, (4) developing workflows and allocating resources, and (5) future recommendations. Participants described innovative strategies for implementing telehealth, such as coordinating interdisciplinary visits with multiple HPPs and inviting informal caregivers (eg, spouse) to participate in telehealth visits. Health care workers discussed key challenges, such as workflow integration, lack of physical exam and biometric data, and overcoming the digital divide (eg, telehealth accessibility among patients with communication-related disabilities). Participants recommended policy advocacy to support telehealth (eg, medical licensure policies) and monitoring how telehealth affects patient outcomes and health care delivery. Conclusions: To support telehealth growth, implementation strategies are needed to ensure that HPPs and patients have the tools necessary to effectively engage in telehealth. At the same time, cancer care organizations will need to engage in advocacy to ensure that policies are supportive of oncology telehealth and develop systems to monitor the impact of telehealth on patient outcomes, health care quality, costs, and equity.

Background: Head-and-neck cancers (hncs) often present at an advanced stage, leading to poor outcomes. Late presentation might be attributable to patient delays (reluctance to seek treatment, for instance) or provider delays (misdiagnosis, prolonged wait time for consultation, for example). The objective of the present study was to examine the length and cause of such delays in a Canadian universal health care setting. Methods: Patients presenting for the first time to the hnc multidisciplinary team (mdt) with a biopsy-proven hnc were recruited to this study. Patients completed a survey querying initial symptom presentation, their previous medical appointments, and length of time between appointments. Clinical and demographic data were collected for all patients. Results: The average time for patients to have their first appointment at the mdt clinic was 15.1 months, consisting of 3.9 months for patients to see a health care provider (hcp) for the first time since symptom onset and 10.7 months from first hcp appointment to the mdt clinic. Patients saw an average of 3 hcps before the mdt clinic visit (range: 1–7). No significant differences in time to presentation were found based on stage at presentation or anatomic site. Conclusions: At our tertiary care cancer centre, a patient’s clinical pathway to being seen at the mdt clinic shows significant delays, particularly in the time from the first hcp visit to mdt referral. Possible methods to mitigate delay include education about hnc for patients and providers alike, and a more streamlined referral system.