Literature DB >> 35761025

Changes in multiple myeloma treatment patterns during the early COVID-19 pandemic period.

Amy J Davidoff1,2, Scott F Huntington3,1, Natalia Neparidze4,5, Rong Wang1,6, Amer M Zeidan3,1, Nikolai A Podoltsev3,1, Rory M Shallis3,1, Xiaomei Ma1,6.   

Abstract

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Year:  2022        PMID: 35761025      PMCID: PMC9243711          DOI: 10.1038/s41375-022-01633-x

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   12.883


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To the Editor:

The COVID-19 pandemic has had dramatic impact on health maintenance and solid cancer screening [1], but its impact on the management of hematologic malignancies is less clear. We selected multiple myeloma (MM), the second most common hematologic malignancy, to evaluate potential changes in clinical presentation and treatment during the COVID-19 pandemic period (COVID). Early in the pandemic professional groups released guidance for changes in MM care, including recommendations to consider prolonging active surveillance, using all-oral regimens, and delaying autologous stem cell transplantation (ASCT) [2-7]. It is unknown whether patients presented with more advanced MM at diagnosis or experienced different patterns of MM treatment during COVID. Our study used the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database containing patient-level data from ~280 community or academic cancer clinics across the US [8, 9], to examine adult MM patients who were newly diagnosed or treated from 2014 to 2020. The Institutional Review Board approved the study, including a waiver of informed consent. We established two analytic cohorts: new patients (NEWPT n = 1319; 964 pre-COVID, 355 COVID) and established patients (ESTABLISHED n = 2206; 1014 pre-COVID, 1192 COVID). NEWPT included adults (age ≥ 18 years) newly diagnosed with MM during February–June in 2018 or 2019 (pre-COVID), or 2020 (COVID) with management (office visit, diagnostic testing, treatment) within 90 days after diagnosis. NEWPT were followed for 7 months from diagnosis, or until death, whichever came first. ESTABLISHED included adults receiving MM maintenance or a second or higher line of treatment (LOT) with an index date (start of treatment) of either 2/1/2017 (pre-COVID) or 2/1/2020 (COVID). To avoid overlap in the two periods, we selected patients diagnosed in 2014–2016 (pre-COVID) and 2017–2019 (COVID), followed to the end of observation year (2017 or 2020) or death, whichever came first. Among NEWPT, we evaluated clinical presentation, Eastern Cooperative Oncology Group performance status (ECOG PS 0-1, 2–4, unknown), anemia/kidney function within 90 days prior to the diagnosis date, manually abstracted ISS stage, heavy/light chain and initial LOT. Time to treatment initiation (TTI) was measured as days from diagnosis to first therapy date. We evaluated receipt of ASCT, chemoimmunotherapy, supportive care (antiviral or bone modifying agents (BMA)). Treatments were grouped into LOTs using oncologist-defined, rule-based lines of therapy [10]. Study covariates included sex, age at diagnosis (≤64, 65–74, ≥75 years), race (White, Black/African American, Hispanic or Latino, other), insurance type, and academic versus community setting. For ESTABLISHED we examined chemoimmunotherapy used in each LOT, oral versus parenteral treatments, ASCT, and clinical trial participation. We employed a pre-post design, comparing presentation and treatment during pre-COVID and COVID for both cohorts. Patient demographic, clinical characteristics, and treatments were compared between pre-COVID and COVID using Pearson’s χ2 test. We used Kaplan-Meier curves and log-rank tests to compare TTI between the two periods. Multivariable Cox proportional hazards regression was used to determine impact of COVID on TTI, with death as a competing risk, adjusting for sex, age, race, insurance type, stage, baseline ECOG PS, and hospital setting. Most patients in both groups were non-Hispanic White; 80% were treated at community cancer clinics. For NEWPT, the median age at diagnosis was 71 (intra-quartile range (IQR) 62–77) years. We observed no differences in baseline stage, ECOG PS, or anemia/kidney function between the two periods (Table 1A). Among NEWPT, 878 (91.1%) pre-COVID and 306 (86.2%) COVID period patients received MM treatment. Compared with the pre-COVID, patients during COVID were less likely to initiate treatment (p < 0.01); and initiated treatment later (Fig. 1A), with a median TTI of 30 (95% confidence interval (CI) 29–32) and 32 (95% CI 29–34) days for pre-COVID and COVID, respectively (p = 0.04). After adjusting for patient demographic and clinical features, we observed a trend towards longer TTI during COVID (COVID vs pre-COVID hazard ratio = 0.88, 95% CI 0.77–1.01, p = 0.06; factors associated with TTI shown in Table 1B). More patients during COVID (80.4%) received IMID-regimens than their pre-COVID counterparts (74.3%, p < 0.01). Few in either period received oral-only regimens (11.0% pre-COVID, 7.8% COVID, p = 0.11). Only 17.3% pre-COVID and 13.7% during COVID received more than one LOT during the observation period (p = 0.14). During pre-COVID 4.8% received monoclonal antibody (mAb), this increased to 14.4% during COVID (p < 0.01) (Fig. 1B). Among patients treated with proteasome inhibitors (PI), 69.0% pre-COVID and 75.2% COVID period patients received antivirals (p = 0.06). There was no difference in ASCT administration during the two periods (14.4% pre-COVID vs 13.4% COVID, p = 0.68).
Table 1

Baseline Patient Characteristics.

A. Baseline clinical features of newly diagnosed MM patients
Pre-COVIDCOVIDp
n (%)n (%)
Total964355
ISS stage
   Stage I223 (23.1)68 (19.2)0.28
   Stage II195 (20.2)80 (22.5)
   Stage III191 (19.8)73 (20.6)
   Unknown355 (36.8)134 (37.7)
ECOG
   0–1228 (23.7)75 (21.1)0.96
   2–434 (3.5)11 (3.1)
   Unknown702 (72.8)269 (75.8)
Hgb (g/L)
   4.9–9.9264 (27.4)89 (25.1)0.43
   10–17.499 (10.3)40 (11.3)
   Unknown601 (62.3)226 (63.7)
Creatinine (mg/dL)
   0.44–1.29228 (23.6)70 (19.7)0.32
   1.30–21.04101 (10.5)39 (11.0)
   Unknown635 (65.9)246 (69.3)
Fig. 1

Time to Treatment Initiation and Regimens.

A Time to treatment initiation (TTI) in days among newly diagnosed patients with MM(NEWPT cohort); pre-COVID n = 878 and COVID n = 306. A trend toward longer TTI during COVID was observed. B Treatment regimens received among patients with newly diagnosed MM during the follow-up in pre-COVID and COVID periods. The use of mAb appeared to increase during COVID period. C Treatment regimens received during follow-up among ESTABLISHED patients with MM in pre-COVID and COVID periods. During COVID, patients received more mAb regimens and less cyclophosphamide compared with pre-COVID period.

Baseline Patient Characteristics.

Time to Treatment Initiation and Regimens.

A Time to treatment initiation (TTI) in days among newly diagnosed patients with MM(NEWPT cohort); pre-COVID n = 878 and COVID n = 306. A trend toward longer TTI during COVID was observed. B Treatment regimens received among patients with newly diagnosed MM during the follow-up in pre-COVID and COVID periods. The use of mAb appeared to increase during COVID period. C Treatment regimens received during follow-up among ESTABLISHED patients with MM in pre-COVID and COVID periods. During COVID, patients received more mAb regimens and less cyclophosphamide compared with pre-COVID period. ESTABLISHED patients had median age 69 (IQR 61–76). During COVID they received more mAb-regimens (28.9% vs 16.9%, p < 0.01) (Fig. 1C), and less cyclophosphamide (7.9% vs 15.1%, p < 0.01) compared with pre-COVID. Patients during pre-COVID were more likely to enroll in a clinical trial (3.3% vs 2.5%, p = 0.03). Oral-only regimens were used in 21.1% and 18.2% in pre-COVID and COVID, respectively (p = 0.09). The receipt of BMA was similar during the two periods for both cohorts: NEWPT 57.6% pre-COVID, 57.8% COVID, p = 0.95; ESTABLISHED 51.5% pre-COVID and 55.6% COVID; p = 0.05. In summary, new MM patients during COVID were less likely to initiate treatment (p < 0.01) and trended towards a longer TTI after adjusting for patient characteristics. The increased frequency of frontline mAb-regimens in NEWPT during COVID likely reflects the influence of landmark publications on the success of novel quadruplet combinations and might not be attributable to the impact of the pandemic [11]. More patients during COVID received IMID-based regimen, reflecting overall less usage of alkylators in the modern era. Notwithstanding the obstacles of the pandemic, care continued for transplant eligible NEWPT within guidelines; they received appropriate chemoimmunotherapy regimens and ASCT during COVID. We demonstrate very low trial participation of MM patients even pre-COVID (3.3%) with further decrease during COVID, underscoring the need to enhance trial participation of MM patients. While other studies have reported delayed/disrupted cancer screening and care during COVID [12-14], our study of real-world adult patients with MM in the US shows little evidence of delayed diagnosis or worsening of clinical presentation, and only modest changes in treatment early during the pandemic. One explanation for this difference is that clinical MM presentation often involves kidney failure, anemia, hypercalcemia, and pathologic bone fractures that must be addressed urgently. Further, the mainstay of MM treatment is systemic chemoimmunotherapy whereas solid tumors are often managed with surgery and/or chemoradiotherapy, which may have presented additional care coordination challenges. Our study is the first report describing patterns of care in MM during early pandemic and is consistent with a prior US study in metastatic cancers wherein the COVID-19 pandemic did not impact TTI or treatment selection [15]. Our study has notable limitations: the pre-post study design cannot address temporal changes in practice unrelated to COVID-19 pandemic, such as new drug approvals, including frontline use of mAbs. Flatiron Health EHR-derived de-identified database may not be fully representative of the entire population of patients with MM in the US across all oncology care settings. Given relatively small sample sizes, we could not test for heterogeneity across patients by race, ethnicity, age, or insurance. We lacked information on patient socioeconomic status and their access to technologies. Further, we focused on the early COVID-19 pandemic. It is plausible that additional practice changes occurred later during the pandemic. Nonetheless, our study captures the experience of a large cohort of MM patients during the early COVID-19 pandemic. Further studies are needed to examine potential effects of COVID-19 on clinical outcomes.
  12 in total

1.  Daratumumab, lenalidomide, bortezomib, and dexamethasone for transplant-eligible newly diagnosed multiple myeloma: the GRIFFIN trial.

Authors:  Peter M Voorhees; Jonathan L Kaufman; Jacob Laubach; Douglas W Sborov; Brandi Reeves; Cesar Rodriguez; Ajai Chari; Rebecca Silbermann; Luciano J Costa; Larry D Anderson; Nitya Nathwani; Nina Shah; Yvonne A Efebera; Sarah A Holstein; Caitlin Costello; Andrzej Jakubowiak; Tanya M Wildes; Robert Z Orlowski; Kenneth H Shain; Andrew J Cowan; Sean Murphy; Yana Lutska; Huiling Pei; Jon Ukropec; Jessica Vermeulen; Carla de Boer; Daniela Hoehn; Thomas S Lin; Paul G Richardson
Journal:  Blood       Date:  2020-08-20       Impact factor: 22.113

2.  Use of Electronic Health Record Data for Quality Reporting.

Authors:  Amy P Abernethy; James Gippetti; Rohit Parulkar; Cindy Revol
Journal:  J Oncol Pract       Date:  2017-07-26       Impact factor: 3.840

3.  Impact of the COVID-19 Pandemic on Treatment Patterns for Patients With Metastatic Solid Cancer in the United States.

Authors:  Ravi B Parikh; Samuel U Takvorian; Daniel Vader; E Paul Wileyto; Amy S Clark; Daniel J Lee; Gaurav Goyal; Gabrielle B Rocque; Efrat Dotan; Daniel M Geynisman; Pooja Phull; Philippe E Spiess; Roger Y Kim; Amy J Davidoff; Cary P Gross; Natalia Neparidze; Rebecca A Miksad; Gregory S Calip; Caleb M Hearn; Will Ferrell; Lawrence N Shulman; Ronac Mamtani; Rebecca A Hubbard
Journal:  J Natl Cancer Inst       Date:  2022-04-11       Impact factor: 11.816

4.  Real-world progression, treatment, and survival outcomes during rapid adoption of immunotherapy for advanced non-small cell lung cancer.

Authors:  Sean Khozin; Rebecca A Miksad; Johan Adami; Mariel Boyd; Nicholas R Brown; Anala Gossai; Irene Kaganman; Deborah Kuk; Jillian M Rockland; Richard Pazdur; Aracelis Z Torres; Jizu Zhi; Amy P Abernethy
Journal:  Cancer       Date:  2019-08-05       Impact factor: 6.860

Review 5.  Multiple Myeloma in the Time of COVID-19.

Authors:  Abdullah S Al Saleh; Taimur Sher; Morie A Gertz
Journal:  Acta Haematol       Date:  2020-04-17       Impact factor: 2.195

6.  COVID-19 and myeloma: what are the implications for now and in the future?

Authors:  Ciara L Freeman; Joseph Mikhael
Journal:  Br J Haematol       Date:  2020-06-25       Impact factor: 8.615

Review 7.  Management of patients with multiple myeloma in the era of COVID-19 pandemic: a consensus paper from the European Myeloma Network (EMN).

Authors:  Evangelos Terpos; Monika Engelhardt; Gordon Cook; Francesca Gay; Maria-Victoria Mateos; Ioannis Ntanasis-Stathopoulos; Niels W C J van de Donk; Hervé Avet-Loiseau; Roman Hajek; Annette Juul Vangsted; Heinz Ludwig; Sonja Zweegman; Philippe Moreau; Hermann Einsele; Mario Boccadoro; Jesus San Miguel; Meletios A Dimopoulos; Pieter Sonneveld
Journal:  Leukemia       Date:  2020-05-22       Impact factor: 12.883

8.  The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study.

Authors:  Camille Maringe; James Spicer; Melanie Morris; Arnie Purushotham; Ellen Nolte; Richard Sullivan; Bernard Rachet; Ajay Aggarwal
Journal:  Lancet Oncol       Date:  2020-07-20       Impact factor: 54.433

9.  Delays and Disruptions in Cancer Health Care Due to COVID-19 Pandemic: Systematic Review.

Authors:  Rachel Riera; Ângela Maria Bagattini; Rafael Leite Pacheco; Daniela Vianna Pachito; Felipe Roitberg; Andre Ilbawi
Journal:  JCO Glob Oncol       Date:  2021-02
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