Introduction: Myeloid malignancies are a heterogeneous group of clonal bone marrow disorders that are complex to manage in the community and therefore often referred to subspecialists at tertiary oncology referral centers. Many patients do not live in close proximity to tertiary referral centers and are unable to commute long distances due to age, comorbidities, and frailty. Interventions that minimize the travel time burden without compromising quality of care are an area of unmet need. We describe a cancer care delivery model for patients with myeloid malignancies that is built around telehealth and enables this vulnerable population access to care at an NCI-designated cancer center while receiving majority of their care close to home. Methods and Materials: We report on a cohort of patients with myeloid malignancies who were co-managed by a general community oncologist and an academic leukemia subspecialist at Montefiore Einstein Cancer Center in New York. Patients were initially referred to our institute for a second opinion by community practices that are in partnership with Montefiore Health System, and initial visits were in-person or via telehealth. Treatment plans were made after discussion with patient’s local community oncologist. Patients then continued to receive majority of their treatment and supportive care including transfusion support with their local oncologist, and follow-up visits were mainly via telehealth with the academic leukemia subspecialist. Results: Our cohort of 12 patients had a median age of 81 years (range, 59–88 years). Patients remained on active treatment for a median time of 357 days (range, 154–557 days). Most of our patients had a performance status of ECOG 2 or higher. Three patients had myelodysplastic syndromes, 7 patients had acute myeloid leukemia, and 2 patients had myelofibrosis. The median number of hospitalizations over the total treatment time period was one. Conclusion: We demonstrate a shared academic and community care co-management model for the treatment of myeloid malignancies in elderly, frail patients using telehealth as a backbone with a very low hospitalization rate.

In March 2020, the COVID-19 pandemic led to a disruption of cancer care due to surging demands for healthcare resources as well as safety measures to control the spread of disease. To limit physical exposure of patients, telemedicine was rapidly adopted as a tool to continue caring for cancer patients. With distance no longer being a limiting factor, elderly and frail cancer patients now had access to a larger provider network to seek opinions for their cancer care.

Myeloid malignancies are a heterogeneous group of clonal bone marrow disorders characterized by clonal proliferation of hematopoietic stem or progenitor cells, recurrent genetic abnormalities, myelodysplasia, ineffective hematopoiesis, peripheral-blood cytopenia, and a varying risk of evolution to acute leukemia [1].They comprise chronic stages such as ineffective hematopoiesis in the form of myelodysplastic syndromes (MDS) and myeloproliferative neoplasms, and a more acute phase of acute myeloid leukemia (AML). The management of myeloid malignancies requires expertise with constant vigilance and readily available supportive care with transfusion of blood products, prevention of infections, and early recognition of sepsis. Analysis of clinical outcomes across diverse practice settings has shown that patients with myeloid malignancies treated at academic or NCI-designated cancer centers with a subspecialty in these disorders have improved outcomes with lower odds of inpatient death or hospice discharge [2, 3].

The treatment landscape of MDS and AML has dramatically changed in the last few years, with the approval of several novel agents for subgroups of patients that harbor specific mutations, and the treatment of elderly patients has been revolutionized with the addition of venetoclax to hypomethylating agents (HMAs) [4]. Therefore, selection of a treatment strategy adapted to an individual patient and disease determinants has become an increasingly complex process. For elderly patients and those with comorbid illnesses who live a distance from academic centers, the travel for treatment can be particularly burdensome and is often a limiting factor in pursuing optimal therapy. We hereby describe a model for cancer care delivery that incorporates input from a subspecialist in myeloid malignancies at an NCI-designated academic center without placing a burden on patients to commute long distances.

Montefiore Einstein Cancer Center is an academic, NCI-designated cancer center in the Bronx, NY. Even though New York State is home to seven NCI-designated cancer centers, most of these are concentrated in New York City. Our cancer center given its location in the Bronx receives referrals from adjoining community practices located in the New York suburbs such as Westchester, Putnam, Duchess, Orange, Rockland, and Ulster counties. These community oncology practices all operate independently but also have a partnership with Montefiore Health System and therefore share the same electronic medical record (EMR). We report a series of patients who received majority of their oncology care for MDS/AML at a community oncology practice with expertise using telehealth from an academic medical oncologist subspecializing in leukemia. All data were reviewed from patients’ EMR charts which capture all data including hospitalizations. We searched our network database for patients who had a myeloid malignancy and received therapy with their local oncologist during the height of the COVID pandemic in NY during the year from March 2020 to 2021.

Patients were either elderly and/or had a poor performance status therefore unable to travel long distances for frequent clinic visits and infusions. Patients were initially referred to our academic center for a second opinion by their primary oncologist for either a new diagnosis or follow-up for their MDS or AML. Initial visits at our academic center were either in person or via telehealth. Pathological review to confirm the diagnosis was also done at our academic center. Treatment plans were formulated in a phone discussion with the patient’s primary oncologist and documented in our shared EMR which enabled easy access for both providers and their teams to see the treatment plan, notes, labs, imaging and pathology data. A limitation of televisit is the inability to examine the patient, so for these visits, the pertinent physical exam findings relied solely on the primary oncologist who saw the patient in person. In cases where patients required emergent care to cytoreduce a hyperproliferative leukemia, they received the first induction at our institution. Otherwise, patients received all care from their local oncologist (including infusions, transfusions, and laboratory checks) at the community oncology practice. Community oncologists were given 24/7 access to communicate with a leukemia physician at our center, using cell phone, EMR, or email. Patients were then followed at eight- to ten-week intervals via televisits with the academic leukemia subspecialist and had in-person visits as needed based on patient preference. We also held biweekly virtual conferences to discuss challenging cases, attended by academic and community oncologists along with hematopathologists. Figure 2 depicts the workflow of our co-management model.

Fig. 2.

Workflow for our co-management model.

Fig. 2.

Workflow for our co-management model.

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Twelve patients were identified from our network database which were co-managed with community oncologists. Patient characteristics are listed in Table 1. Median age was 81 years (range, 59–88 years). Median time patients remained on treatment was 357 days (range, 154–557 days). Figure 1 shows a New York State map with locations of our academic center with respect to community oncologists’ offices and patients’ home zip codes. Patients were treated at six different sites and lived in six different counties across New York State. The median number of telehealth visits was 3 and in-person visits was 3.5. Eight of the 12 patients had a performance status of 2 or higher. The median number of hospitalizations during treatment period was 1 (range 1–3). Three patients had MDS, 7 patients had secondary AML (four transformed from MDS, one from myeloproliferative neoplasm, and one transformed from essential thrombocythemia), 2 patients had myelofibrosis. Of the 7 patients with AML, five were treated with a combination of venetoclax and HMA – azacitidine or decitabine. Two patients harbored targetable mutations (IDH1 and FLT3) and received targeted agents (ivosidenib and gilteritinib) in addition to the HMA/venetoclax backbone. Four patients with MDS were treated with HMAs (azacitidine or decitabine). All patients required dose reductions and interruptions for adverse events, and these decisions were made jointly by the local and academic oncologists. One patient with myelofibrosis received his initial treatment with HMA/venetoclax with his local general oncologist followed by an allogeneic stem cell transplant at our institution.

Table 1.

Patient characteristics

 Patient characteristics
 Patient characteristics
Fig. 1.

Map showing approximate location of patient address and community and academic oncology clinic.

Fig. 1.

Map showing approximate location of patient address and community and academic oncology clinic.

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The treatment paradigm for myeloid malignancies is rapidly evolving with the approval of over ten novel agents in the past 5 years and multiple other investigational approaches in the pipeline [5, 6]. Many of these new agents have a unique toxicity profile which is not seen in other malignancies and have added to the already high level of complexity in managing these patients in the community setting [7]. This is reflected in two recent studies showing a significantly lower mortality in patients treated at high-volume centers. Bhatt et al. [3] evaluated outcomes for AML patients from a national cancer database and showed the 1-month mortality rate was 16% for patients treated at academic centers versus 29% in nonacademic centers (p < 0.01), and even more impressive were the differences in 5-year overall survival (15 vs. 25%, p < 0.01). Similarly, a study from California reported that after adjustment for baseline characteristics, treatment at an NCI-designated cancer center was associated with a lower early mortality (OR: 0.46, CI: 0.38–0.57) [2]. However, majority of patients with myeloid malignancies are elderly and live far from academic and NCI-designated centers.

The COVID-19 pandemic has led to rapid improvements in virtual platforms such as telehealth, and reimbursement is now being offered for this service [8]. We demonstrate that combining telehealth with real-time input and oversight by subspecialty oncologists at academic centers allows for delivery of complex myeloid malignancy care at community centers, without patients having to travel long distances. Prior studies have shown that long travel distance to treatment centers negatively impacts the quality of life (QoL) and can be a barrier to accessing care. Patients who live far and need to travel over 50 miles for treatment are known to have lower adherence to treatment and a worse QoL [9]. Compared to other malignancies, older patients with myeloid malignancies require frequent visits to health care facilities for clinical and laboratory monitoring and therefore bear a higher cost for travel. Recent reports suggest that even in era of novel agents, elderly patients with AML spent nearly half their days engaged in oncology care which is 4 times the amount of time for patients with solid tumors who have a similar prognosis [10].

The good outcomes in our cohort are reflected by the median of one hospitalization while on treatment, which compares favorably with published data for this age group [11]. The lower hospitalization rate cuts cost and more importantly adds to QoL, as prior studies have shown worsening of depression and overall QoL for patients and their caregivers during hospitalization [12].

Several other mechanisms of second opinion and co-management in oncology care exist informally, though these have not been published in the literature. A similar co-management strategy between academic institutes and community centers in Georgia for acute promyelocytic leukemia has shown a decrease in early mortality as compared to population-based registry [13]. West et al. [14] describe their experiences with a pilot program (“AccessHope”) that offers remote subspecialist input in thoracic oncology in which second opinions identified evidence-based management changes affecting current treatment in 28% and potential improvements to care in 92% of patients, as well as cost savings realized by eliminating low-value interventions.

Our proposed care delivery model enables patients to not just obtain a second opinion but also a framework for follow-up care using telemedicine as well as collaboration with local oncologists to formulate and implement complex treatment plans. Of note, many of the recently FDA-approved drugs for myeloid malignancies are oral agents (such as venetoclax, oral azacitidine, IDH inhibitors, oral decitabine/cedazuridine), thereby making it easier to manage these patients via telehealth [15].

Limitations to our study are the small cohort and the retrospective nature of this review which may be biased toward patients who are well enough clinically to establish a co-management relationship. The small size also limits the ability to evaluate outcomes for patients who have no in-person visits at a tertiary center.

In conclusion, we demonstrate a shared academic and community care co-management model for the treatment of myeloid malignancies in elderly, frail patients using telehealth as a backbone with a low rate of hospitalization. Elderly patients with myeloid malignancies should have the ability to get care close to their homes, despite having a challenging disease that has conventionally been treated at tertiary academic centers.

This study protocol was reviewed and approved by the Institutional Review Board at the Albert Einstein College of Medicine, approval number – 2021-13355. Given the retrospective nature of this study, the need for informed consent was waived by Institutional Review Board at the Albert Einstein College of Medicine. Our study was conducted ethically in accordance with the World Medical Association Declaration of Helsinki.

Niyati Goradia, Mendel Goldfinger, Ira Braunschweig, Kira Gritsman, Nishi Shah, Monica Comas, Susan Fox, Marina Konopleva, Eric Feldman, and David Levitz have no conflicts of interest to declare. Aditi Shastri has received research funding from Kymera Therapeutics, consultancy fees from Jansen Pharmaceuticals, and honoraria from Rigel pharmaceuticals and OncLive. Alejandro Sica has received consultancy fees from Miragen, Kite Pharma, and Curio; research funding from Bristol Myers Squibb Foundation Diversity in Clinical Trials Programs Scholar Award and also serves as a faculty advisor for PER (physicians education review). Amit Verma has received research funding from Prelude, BMS, GSK, Incyte, Medpacto, Curis, and Eli Lilly; is a scientific advisor for Stelexis, Bakx, Novartis, Acceleron, and Celgene; received honoraria from Stelexis and Janssen; and holds equity in Stelexis, Bakx, and Throws Exception. Ioannis Mantzaris serves on the KITE ALL advisory board.

This research did not have any funding sources.

The authors confirm contribution to the paper as follows. Study conception and design: Niyati Goradia, Mendel Goldfinger, Amit Verma, and Aditi Shastri; data collection: Niyati Goradia, Aditi Shastri, Alejandro Sica, Kira Gritsman, Ioannis Mantzaris, Monica Comas, Ira Braunschweig, Noah Kornblum, Nishi Shah, Marina Konopleva, and Eric Feldman; analysis and interpretation of results: David Levitz, Niyati Goradia, Noah Kornblum, Nishi Shah, Susan Fox, and Dennis Cooper; draft manuscript preparation: Niyati Goradia, Mendel Goldfinger, Amit Verma, Kira Gritsman, Ira Braunschweig, Ioannis Mantzaris, Noah Kornblum, Monica Comas, Marina Konopleva, Alejandro Sica, and Eric Feldman. All authors reviewed the results and approved the final version of the manuscript.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

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