Regionalization of Acute Myeloid Leukemia Treatment in a Community-Based Population: Implementation and Early Results



 

Lisa Y Law, MD1; Stephen P Uong, MS2; Hyma T Vempaty, MD3; Vu H Nguyen, MD4; David Baer, MD4; Vincent X Liu, MD2; Lisa J Herrinton, PhD2

Perm J 2021;25:20.271

https://doi.org/10.7812/TPP/20.271
E-pub: 03/17/2021

ABSTRACT

Introduction: Regionalization of care for acute myeloid leukemia (AML) has not been described for community-based settings. In 2015, we shifted AML induction from 21 local centers to 3 regional centers.

Methods: Using time-specific inception cohorts, we assessed whether regionalization was associated with the frequency of use of induction therapy, receipt of bone marrow transplantation, 60-day mortality (treatment toxicity), and 180-day mortality (treatment effectiveness). Information for all adult patients diagnosed with AML from 2013 to 2017 was obtained from the electronic health record. Multivariable methods were used to estimate the adjusted associations of induction, bone marrow transplantation, and death in relation to year of diagnosis before and after regionalization.

Results: Of 661 patients diagnosed during 2013 to 2017, 53% were ≥ 70 years, 22% were ≥ 80 years, and 10% died within the week following diagnosis. Comparing 2017 with 2013, the proportion of patients who received induction therapy increased 2.88 times (95% confidence interval [CI] = 1.55-5.35), and the proportion of non-acute promyelocytic leukemia patients receiving bone marrow transplantation increased 2.00 times (95% CI = 0.89-4.50). Regionalization was associated with lower 180-day mortality (hazard ratio [HR] = 0.64; 95% CI = 0.44-0.92), whereas change in 60-day mortality was not statistically significant (HR = 0.67; 95%CI = 0.43-1.04).

Conclusion: In this community-based population, many patients were of advanced age yet benefitted from AML induction therapy delivered at a regionally specialized center. These early results suggest the benefit of regionalizing subspecialty leukemia care.

INTRODUCTION

The incidence of acute myeloid leukemia (AML) rises sharply with age, and most patients with AML are elderly and have substantial comorbidities.1 Intensive induction followed by consolidation with further chemotherapy or bone marrow transplantation is the standard of care for patients who can tolerate its toxicities,2 which many of the oldest patients cannot.3 Thus, a key challenge in the management of AML is patient assessment and appropriate selection of therapy to balance life expectancy, complications, and quality of life.4

In 2015, Kaiser Permanente Northern California began establishing a regional care pathway to improve AML management. Before regionalization, AML patients were managed by community-based hematologic oncologists at 21 local centers. After regionalization, new AML patients were first triaged by 1 of the 15 leukemia subspecialists at 1 of the 3 regional centers to assess each patient’s fitness to tolerate induction. Patients who were fit and who agreed to induction were then treated at a regional center; others received palliative care locally.

We conducted a longitudinal cohort study using inception cohorts to assess the association of year of diagnosis with the frequency of use of induction therapy, bone marrow transplantation, 60-day mortality (a measure of treatment toxicity), and 180-day mortality (a measure of treatment effectiveness). To avoid selection bias, we did not directly compare regionally treated patients with locally treated patients because regionally treated patients were selected based on their fitness to tolerate treatment and would have a lower risk of death at baseline that could not be adequately controlled in the statistical analysis. Instead, we compared changes over time, reasoning that on average, inception cohorts of AML patients diagnosed each calendar year were similar and did not differ systematically. Thus, the study examined time trends in treatment and outcomes during 2013 to 2017, using the premise that treatment trends stemmed from regionalization while recognizing that global changes in evidence and adoption could result in trends as well. We hypothesized that later year of diagnosis would be associated with increased use of induction and receipt of bone marrow transplantation and lower mortality.

MATERIALS AND METHODS

This project was determined by the National Compliance Officer of the Kaiser Foundation Research Institute as not meeting the regulatory definition of human subjects research.

Setting

The longitudinal cohort study was set at Kaiser Permanente Northern California, a comprehensive, integrated healthcare delivery system that serves one-third of the population, or 4.4 million members, at its 21 medical centers. The membership has been well characterized for research and represents the underlying population but underrepresents the very poor and the very wealthy.5 Between 2013 and 2017, the adult membership shifted to become slightly younger (aged 18-59, 75.6% in 2013 vs 79.9% in 2017) and more racially diverse (non-White, 53.6% in 2013 vs 55.5% in 2017).

Regional Care Pathway

Implementation of regional care began in 2015 following agreements made among the medical group’s 21 oncology departments. Because most AML patients present with critical disease, referral to 1 of 3 regional leukemia centers is made through an urgent phone call. During the call, the local hematologist and 1 of 15 regional leukemia subspecialists review the patient’s medical record; discuss clinical status, performance status and comorbidities; and assess the patient’ ability to tolerate low- or high-intensity induction chemotherapy toward the goal of extending survival. If the leukemia subspecialist judges the patient as able to tolerate intensive induction, then the patient is immediately transferred. A common triage tool used is the on-line AML score,6 which estimates treatment-related mortality (ie, risk of death by 60 days based on various characteristics and measurements). Once referred, the patient is formally evaluated by a leukemia subspecialist to assess eligibility for induction therapy. Patients deemed fit are admitted and cared for by the leukemia service hematologist-oncologist, hospitalist, nurse, pharmacist, social worker, patient care coordinator, and clinical educator who have training and experience caring for acutely ill AML patients. The patients also receive care from experts in transfusion medicine, infectious diseases, and critical care. A clinical trial coordinator evaluates each patient’s eligibility for participation in national clinical trials. The 15 leukemia subspecialists conference monthly to discuss care protocols and pathways. They also meet weekly to review cases and patient status. A multidisciplinary round takes place daily, during which patients are evaluated by a team including a clinical educator, a patient care coordinator, and a medical social worker. All eligible patients are referred for bone marrow transplant; the majority of bone marrow transplants are performed by Stanford University Medical Center.

Patients deemed ineligible for high-intensity induction usually are not transferred to the regional center. However, some patients are transferred, found to be unfit for intensive therapy, started on low-intensity induction, and then transferred back to the local center for subsequent treatment. Patients who are not fit for induction or transfer or who decline (< 5%) are managed locally toward the goal of palliation. Thus, the regional centers disproportionately and by design manage patients who are younger and have fewer comorbidities, have better performance status, and are more likely to survive to 60 days.

Study Population

The study population included adults newly diagnosed with AML (ICD-O-3 histology codes 9805-9809, 9840-9861, 9865-9874, and 9891-9931) between January 2013 and December 2017.7 Cases were identified from the Kaiser Permanente Northern California Cancer Registry.8 To ensure adequate information about baseline health status, we restricted the study to patients with at least 1 year of enrollment before their AML diagnosis date but made no other restrictions.

Data Collection

Information was obtained from the health plan’s electronic health record. Regional care was defined as care by 1 of the 15 leukemia subspecialists identified with the regional program. Induction therapy starting within 30 days of diagnosis was identified from medication files. Induction was classified separately for acute promyelocytic leukemia (APL) and non-APL. For APL, we identified all-trans retinoic acid with arsenic or anthracycline. For non-APL, we separately assessed high-intensity and low-intensity therapies,9 and receipt of bone marrow transplantation. The latter was identified from procedure codes recorded within 180 days after the diagnosis and from transplant history codes recorded within 365 days after diagnosis (see Supplemental Materiala). We identified deaths from health plan mortality data and Social Security Administration data, which were complete through December 31, 2017. We also assessed nonfatal complications during the 60 days after diagnosis using ICD-10 diagnostic codes recorded in hospitalization data (see Supplemental Materiala). It is important to keep in mind that the year 2015, when regionalization was initiated, was the same year that diagnostic and procedural coding was switched from the 9th to the 10th edition of the International Classification of Diseases (ICD),10 with the ICD-10 containing many more codes than the ICD-9.

Demographic information was obtained from membership data. Neighborhood deprivation index was calculated using geocoded addresses and American Community Survey data.11 The COmorbidity Point Score (COPS) comorbidity score was developed at Kaiser Permanente Northern California and is computed from 70 diagnostic groups recorded in the year before AML diagnosis and defined by the Centers for Medicare and Medicaid Services as Hierarchical Condition Categories and include sepsis, pneumonia, infection, acute myocardial infarction, cardiac arrest, acute cardiovascular disease, other cardiac conditions, renal failure, cancer, liver and pancreatic diseases, cancer, trauma, and other conditions associated with death.12-15 The COPS score is calibrated for inpatient mortality, with a score of 50 being associated with mortality risk of < 1%, a score of 100 with 5% mortality, and a score of 145 with 10% mortality.13 The Hierarchical Condition Categories are used for Medicare risk adjustment,16 and the COPS score has been validated.14 Infection at diagnosis was determined from hospital admission diagnoses of sepsis, pneumonia, or other infection during the 15-day period before the date of AML diagnosis, inclusive. Baseline white blood cell count at AML diagnosis or in the preceding 30 days was obtained from laboratory data. Baseline estimated glomerular filtration rate was calculated using the CKD-EPI equation17 and the most recent measurement of serum creatinine and was dichotomized as ≤ 29.9 vs ≥ 30 mL/min/1.73 m2. We also identified patients with APL, therapy-related myeloid neoplasm, mixed phenotype acute leukemia, unspecified myeloid leukemia, antecedent myelodysplastic syndrome, or chronic myeloid leukemia in blast crisis using information from the cancer registry.

Statistical Analysis

In bivariate analyses, we compared population proportions of baseline characteristics, induction therapy, bone marrow transplantation, and mortality. These analyses combined cases diagnosed in 2013 and 2014, before the start of regionalization, and combined those diagnosed in 2016 and 2017, when regionalization was well underway. We used the χ2 test to assess statistical significance. To calculate the actuarial incidence of death per 100 patient-months, we began follow-up on the patient’s diagnosis date and ended follow-up on the earliest of the date of death, disenrollment, 60 or 180 days, or the end of the mortality data on December 31, 2017. In multivariate logistic regression analysis, we estimated the odds ratio (OR) and 95% confidence interval (CI) for the association of year of diagnosis with receipt of induction therapy in all AML patients and bone marrow transplantation in non-APL patients after adjusting for age at diagnosis, sex, race/ethnicity, neighborhood deprivation index, the COPS comorbidity score, elevated white blood cell count, and infection at diagnosis. In multivariate proportional hazards analysis, we estimated the adjusted hazard ratio (HR) and 95% CI for the association of year of diagnosis with the mortality rate at 60 and 180 days. Subgroup analyses were performed to assess bivariate associations in relation to age (18-59, 60-69, 70-79, ≥ 80 years). To understand selection of patients for induction, we also compared patients diagnosed in 2016 and 2017 who were selected for regional versus local treatment (see Supplemental Materiala). Analyses were performed using SAS 9.4 and R 3.5.2.

RESULTS

Study Population

We identified 755 adults who were newly diagnosed with AML during 2013 to 2017. Of these, 94 did not have 1 year of baseline enrollment before diagnosis and were excluded, leaving 661 (88%) who were eligible for the study. During 2016 to 2017, 114 patients received local care, and 135 received regional care.

Baseline Characteristics

Patients diagnosed in 2013 and 2014 were similar to those diagnosed in 2016 and 2017 with respect to age, sex, race/ethnicity, baseline white blood cell count, infection at diagnosis, and estimated glomerular filtration rate (Table 1). Patients diagnosed in 2016 and 2017 were more likely to be married or partnered (p < 0.05). They also had greater COPS scores (p < 0.05), although this likely stemmed from changes in ICD coding.

Table 1. Baseline characteristics, treatment, and mortality of patients by year, %

Characteristica 2013-2014 (n = 278) 2016-2017 (n = 249)
Year of diagnosis
 2013 135 (48.6%) -
 2014 143 (51.4%) -
 2015 - -
 2016 - 119 (47.8%)
 2017 - 130 (52.2%)
Leukemia subtype
 De novo AML (none of the below) 215 (77.3%) 199 (79.9%)
 Antecedent MDS 25 (9.0%) 21 (8.4%)
 Secondary AML 6 (2.2%) 1 (0.4%)
 APL 23 (8.3%) 19 (7.6%)
 CML in blast crisis 5 (1.8%) 4 (1.6%)
 Mixed phenotype acute leukemia 1 (0.4%) 1 (0.4%)
 Unspecified myeloid leukemia 5 (1.8%) 4 (1.6%)
Age at diagnosis, y
 18-59 72 (25.9%) 57 (22.9%)
 60-69 56 (20.1%) 60 (24.1%)
 70-79 82 (29.5%) 86 (34.5%)
 ≥ 80 68 (24.5%) 46 (18.5%)
Sex
 Female 124 (44.6%) 120 (48.2%)
 Male 154 (55.4%) 129 (51.8%)
Race/ethnicity
 Asian 30 (10.8%) 40 (16.1%)
 Black 17 (6.1%) 21 (8.4%)
 Hispanic, any race 31 (11.1%) 28 (11.2%)
 White 188 (67.6%) 145 (58.2%)
 Other/unknown 12 (4.3%) 15 (6.0%)
Partner status
 Married, partnered 151 (54.3%) 160 (64.3%)
 Single, divorced, widowed 97 (34.9%) 75 (30.1%)
 Other/unknown 30 (10.8%) 14 (5.6%)
Neighborhood deprivation indexc
 Quartile 1, least deprived 68 (24.5%) 64 (25.7%)
 Quartile 2 71 (25.5%) 61 (24.5%)
 Quartile 3 74 (26.6%) 58 (23.3%)
 Quartile 4, most deprived 65 (23.4%) 66 (26.5%)
COPS scored
 Quartile 1 (0-35) 82 (29.5%) 46 (18.5%)
 Quartile 2 (36-69) 65 (23.4%) 69 (27.7%)
 Quartile 3 (70-104) 68 (24.1%) 64 (25.7%)
 Quartile 4 (105-284) 64 (23.0%) 70 (28.1%)
White blood cell count
 > 100,000 32 (11.7%) 27 (11.1%)
Infection at diagnosise
 Yes 78 (28.1%) 63 (25.3%)
eGFR at diagnosis
 ≤ 29.9 mL/min/1.73 m2 24 (8.3%) 17 (6.8%)
Treatmentf
 APL induction therapy, 0-30 d n = 23 n = 19
 ATRA + arsenic 9 (39.1%) 9 (47.4%)
 ATRA + anthracycline 7 (30.4%) 2 (10.5%)
 Other regimen 3 (13.0%) 4 (21.1%)
 No induction 4 (17.4%) 4 (21.1%)
Non-APL induction therapy, 0-30 d n = 255 n = 230
 High intensity    
  7+3 77 (30.2%) 68 (29.6%)
  FLAG 2 (0.8%) 22 (9.6%)
  MEC 1 (0.4%) -
 Low intensity    
  Azacitidine 38 (14.9%) 51 (22.2%)
  Decitabine 5 (2.0%) 6 (2.6%)
  Other regimen 2 (0.8%) 3 (1.3%)
  No induction 130 (51.0%) 80 (34.8%)
 Bone marrow transplant 43 (16.9%) 51 (22.2%)
Proportion who died, 0-60 dg
 All patients 94 (33.8%) 78 (33.9%)
 APL only 4 (17.4%) 6 (31.6%)
 Non-APL only 90 (35.3%) 72 (34.1%)
Proportion who died, 0-180 dg
 All patients 141 (50.7%) 92 (47.7%)
 APL only 4 (17.4%) 7 (43.8%)
 Non-APL only 137 (53.7%) 85 (48.0%)

a. Nine patients were missing a white blood cell count and 3 were missing an eGFR measurement.

b. Includes history of solid cancer (other than nonmelanoma skin cancer) or myelodysplastic syndrome (9980, 9982-9987, 9989, 9991-9992) using information from the beginning of the cancer registry in 1973, mixed phenotype acute leukemia (9805-9809), and therapy-related myeloid neoplasm (9920).

c. Values that are more positive represent greater deprivation. Quartile ranges: Q1: −1.60 to < −0.85, Q2: −0.85 to < −0.50, Q3: −0.50 to < 0.07, Q4: 0.07-3.00.

d. As regionalization was initiated in 2015, the same year as the ICD-9 to ICD-10 code transition, the elevated COPS score may be related to changes in ICD coding.

e. Recorded during the 15 d before the diagnosis of AML using ICD-9 diagnosis codes 001.X-139.X excluding 038 and ICD-10 diagnosis codes A00-B99 excluding A40 and A41.

f. Only the first cycle of therapy is shown. 7+3 includes cytarabine and anthracycline ± midostaurin; FLAG includes cytarabine, and fludarabine ± anthracycline; MEC includes cytarabine, mitoxantrone, and etoposide.

g. For this table, the analysis of 60-d mortality included patients diagnosed before November 2017, and the analysis of 180-d mortality included patients diagnosed before July 2017.

AML = acute myeloid leukemia; APL = acute promyelocytic leukemia; ATRA = all-trans retinoic acid; CML = chronic myeloid leukemia; EGFR = estimated glomerular filtration rate; MDS = myelodysplastic syndrome.

Treatment and Outcomes

Among the 42 patients with APL, we observed no change over time in the likelihood of initiating induction chemotherapy within 30 days (2013-2014, 82.6%; 2016-2017, 78.9%; p = 0.73) (Table 1). However, among the 485 patients with non-APL, use of induction chemotherapy increased (2013-2014, 49.0%; 2016-2017, 65.2%; p < 0.001), with FLAG ± anthracycline and azacitidine accounting for most of this increase. In multivariable analysis, diagnosis in 2017 compared with 2013 was associated with an increased odds of initiating induction therapy within 30 days (odds ratio [OR] = 2.88; 95% CI = 1.55-5.35) (Table 2 and Supplemental Table 1a) and was associated with an increased odds of bone marrow transplantation (OR = 2.00; 95% CI = 0.89-4.50) (Table 2), although the latter may have resulted from chance.

Table 2. Adjusted associationsa of patient and disease characteristics with initiation of induction therapy, referral for bone marrow transplantation, and mortality at 60 and 180 d, 2013-2017 (N = 661)

    Induction therapy within 30 d Bone marrow transplantationb 60-d mortality 180-d mortality
Year of diagnosisa % OR (95% CI) OR (95% CI) HR (95% CI) HR (95% CI)
2013 20 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.) 1.00 (Ref.)
2014 22 1.11 (0.61-2.00) 0.88 (0.39-1.99) 0.91 (0.60-1.38) 0.87 (0.62-1.22)
2015 20 1.94 (1.05-3.57) 0.99 (0.44-2.25) 0.99 (0.65-1.52) 0.88 (0.62-1.24)
2016 18 1.83 (0.98-3.41) 0.97 (0.42-2.29) 1.06 (0.68-1.65) 0.91 (0.64-1.32)
2017 20 2.88 (1.55-5.35) 2.00 (0.89-4.50) 0.67 (0.43-1.04) 0.64 (0.44-0.92)

a. The models were adjusted for age at diagnosis (18-59, 60-69, 70-79, ≥ 80 y), acute myeloid leukemia type (estimated glomerular filtration rate [APL], non-APL), sex (female, male), race/ethnicity (white, other), neighborhood deprivation index (continuous), COPS score (quartiles), estimated glomerular filtration rate (eGFR) ≤ 29.9 mL/min/1.73 m2 (no, yes), infection at diagnosis (no, yes), and white blood cell count > 100,000/µL (no, yes). One patient was missing information on the neighborhood deprivation index, 12 on white blood cell count, and 6 on eGFR.

b. Restricted to non-APL patients only. Patients aged ≥ 80 y were excluded from the model because they were not eligible to receive a referral for bone marrow transplantation.

c. Neighborhood deprivation index had median −0.5 with interquartile range 0.9. See Supplemental Materiala for full model results.

CI = confidence interval; HR = hazard ratio; OR = odds ratio.

Of the entire cohort of 661 patients, 10% died within a week of diagnosis. Throughout 2013 to 2017, the proportion of patients who died by 60 days was 34.4% for all ages and 45.1% among patients aged ≥ 66 years. The proportion who died by 180 days was 50.1% for all ages and 63.9% among patients aged ≥ 66 years. About one-third of patients died within 60 days, and one-half of patients died within 180 days. In bivariate analyses, these proportions did not differ between 2014 to 2015 and 2016 to 2017 (Table 1). We also conducted multivariable analyses that accounted for loss to follow-up and for confounding by AML type (APL, non-APL), age at diagnosis, sex, race/ethnicity, neighborhood deprivation index, the COPS comorbidity score, elevated white blood cell count, and infection at diagnosis. In these analyses, the risks of death by 60 and 180 days were lower in 2017 compared with 2013 (60-day: HR = 0.67; 95% CI = 0.43-1.04; 180-day: HR = 0.64; 95%CI = 0.44-0.92) (Table 2), although the 60-day association may have resulted from chance.

Subgroup analyses stratified by age suggested that induction increased most in the oldest patients, bone marrow transplantation increased in younger patients, and mortality declined in the oldest age group (Figure 2; Supplemental Figure 1a), although the number of patients available for subgroup analysis was limited, and none of these differences was statistically significant.

 tpj20271f1 copy

Figure 1. Kaplan-Meier plot of survival after AML diagnosis in relation to year of diagnosis, Kaiser Permanente Northern California, 2013-17*. *Log-rank test p = 0.41.

tpj20271f2

Figure 2. Time trends in (A) induction, (B) bone marrow transplantation, (C) 60-day mortality, and (D) 180-day mortality, by age group. The plots above show percentages of patients who (A) received induction therapy within 30 days of AML diagnosis, (B) received bone marrow transplant (patients aged 80 or older were not eligible for bone marrow transplant), (C) died within 60 days of AML diagnosis, or (D) died within 180 days of AML diagnosis.

During 2016 to 2017 when the ICD-10 was used to recorded diagnoses, the overall incidence rates of complications per 100 person-months were as follows: sepsis, 30 (95% CI = 23-36); pneumonia, 23 (95% CI = 17-28); other infection, 30 (95% CI = 23-36); major bleeding, 9 (95% CI = 6-12); respiratory failure, 8 (95% CI = 5-11); and embolism and thrombosis, 7 (95% CI = 4-10).

DISCUSSION

In 2015, Kaiser Permanente Northern California began implementing a regional care pathway such that patients who were eligible for AML induction therapy were referred to 3 regional centers staffed by 15 leukemia subspecialists. We show that over time, more patients, including the elderly, received induction therapy, particularly the reduced-intensity regimen azacitidine, among non-APL patients. Reduced-intensity induction regimens are consistent with contemporary evidence-based medicine, offering a therapeutic option for elderly patients with the goal of prolonging survival and maintaining good quality of life.18 Coincident with these changes, we observed reductions in 60- and 180-day mortality, although the former CI was somewhat wide. Sixty-day mortality is a measure of treatment toxicity, whereas 180-day mortality also captures the benefit of treatment.

The timing of regionalization of care for AML patients took place around the same time that adoption of reduced-intensity induction regimens was increasing among community-based oncologists. It is difficult to assess whether these regimens would have been adopted consistently without the extra effort of regionalization. If so, the effect of regionalization may be lower than we have estimated. However, the magnitude of change in mortality over the course of the study was larger than would be expected from the choice of regimen alone, and other changes resulting from regionalization likely were beneficial as well.

Comparing the present study with past population-based reports is challenging. The oldest patients are often ineligible for intensive treatments yet have a high risk of death.19 Most studies lumped these patients into groups that concealed differences in eligibility for intensive treatment. Ho et al20 compared 60-day mortality among 7007 non-APL patients treated with chemotherapy within 30 days of diagnosis at National Cancer Institute-designated cancer centers or community settings during 1999 to 2014. Patients treated in the community were older (≥ 66 years: 40% vs 26%; p < 0.0001) and were more likely to have ≥ 3 comorbidities (41% vs 30%; p < 0.0001) than those treated at cancer centers. Mortality at 60 days among all ages was 24% in those treated in the community and 12% in those treated at cancer centers (p < 0.001).21 A similar study by the same authors of 30-day mortality among all APL patients treated in California found that 27% died within 30 days.22 The study we report used different exclusion criteria than the statewide study resulting in a much older study population (age ≥ 66 years: statewide study, 36%; present study, 63%), and among those aged ≥ 66 years seen in any setting, 60-day mortality was 36% in the statewide study and 45% in the present study.

Thompson et al23 studied the 2013 Medicare fee-for-service population (aged ≥ 65 years) of 7568 AML patients. At 30 days, risk-adjusted mortality was 32% in low-volume hospitals (2 cases per year) and 28% in very-high-volume hospitals (25 cases per year). A strength of the study was its use of the Medicare cohort, which accurately represented the oldest-old population, who constitute the majority of AML patients and who are underrepresented in many studies. High-volume centers may have better outcomes due to greater resources and staff experience that improve patient assessment, tailored chemotherapy, and management of side effects, particularly in the oldest-old population.23,24

Our findings of increased use of induction chemotherapy and bone marrow transplant among older patients combined with a seeming reduction of treatment-related and longer-term mortality are encouraging, but these results are early and suggestive. Overall survival data to 180 days are not adequate for drawing conclusions about long-term survival, and further study is needed.

Moving forward, we plan additional steps to improve care delivery and outcomes. Ongoing initiatives include developing specific criteria for recommending specific treatment regimen (ie, high-intensity vs low-intensity induction vs targeted therapy), better documenting systemic triage, ensuring high-quality and high-yield physician conferences, improving coordination of care and follow-up of patients treated at local centers, and better evaluating patient preferences and satisfaction. We are also discussing implementation of telemedicine for patients’ long-term follow-up after they return to their local centers to ensure continuity and survivorship care.

Observational studies generally provide poor evidence for treatment effectiveness because patients treated regionally and locally are not comparable. It was for this reason that we analyzed time-specific inception cohorts, reasoning that, on average, the underlying indications for treatment and ability to tolerate treatment did not change over the short period of the study. However, if patients diagnosed with AML during 2013 and 2014 differed from those diagnosed during 2016 and 2017, then the study may have under- or overestimated any benefits resulting from regional care. Indeed, we believe that more patients received molecular testing and targeted therapy in recent years, and this may have improved the prognosis, although we doubt this could explain the entire benefit we observed.

Other limitations should be considered as well. The changes in ICD coding from ICD-9 and ICD-10 likely caused an artefactual increase in comorbidity score, an effect we are seeing across our research studies, because ICD-10 requires more coding than ICD-9. Similarly, patients with more healthcare contacts have greater opportunities for coding comorbidities and complications, whereas those who enter hospice or palliative care likely have less documentation.

Regionalization of surgical oncology services has been described in Canada and the Veterans’ Administration, with the former noting benefits particularly to older patients with lung cancer and the latter noting increased use of therapy overall in the hepatopancreaticobiliary system.25,26 In our setting, an additional benefit of regionalization was the greater opportunity for patients to participate in national clinical trials because of the logistical support available in the regional care setting.

In conclusion, we observed an association of regionalization with increased utilization of induction therapy and bone marrow transplantation and decreased 180-day mortality and possibly 60-day mortality. The treatment of AML has evolved during the past 3 years, with at least 8 new drugs being FDA approved and with each drug having unique adverse-effect profiles. As AML treatment becomes lengthier and more complicated, increased specialization will be required to deliver appropriate care tailored to the patient’s indications and tolerance. We believe that regionalization will benefit AML patients during their initial treatment phase, but because treatment can last for months, ongoing collaboration between the regional and local levels ultimately may provide the best care in the future. Collaborative models should be tested to assure excellent treatment that is accessible to the patient.

Disclosure Statement

The investigators are partners and staff of The Permanente Medical Group and report no other conflicts of interest.

Author Contributions

Lisa Law, MD, assisted in study design, data analysis, and manuscript preparation (drafting and critical review); Stephen Uong assisted in data collection, data management, data analysis, and critical review; Hyma Vempaty assisted in data analysis and drafting of the final manuscript; David Baer assisted in analysis of data and drafting of the final manuscript; Vincent Liu assisted in critical review and drafting of the final manuscript; Lisa Herrinton assisted in study design, data analysis, drafting, and critical review of the manuscript. All authors have given final approval to the manuscript.

Funding

This project was supported by The Permanente Medical Group Delivery Science and Applied Research initiative. Dr Vincent X Liu was further supported by the National Institute of General Medical Sciences under grant number NIH R35GM128672.

Past Presentations

None.

Supplemental Material

aSupplemental Material is available at: www.thepermanentejournal.org/files/2021/20.271supp.pdf.

 Abbreviations

AML = acute myeloid leukemia; APL = acute promyelocytic leukemia; CI = confidence interval; HR = hazard ratio; OR = odds ratio.

Author Affiliations

1Department of Oncology, Roseville Medical Center, Kaiser Permanente Northern California, Roseville, CA

2Division of Research, Kaiser Permanente Northern California, Oakland, CA

3Department of Oncology, Santa Clara Medical Center, Kaiser Permanente Northern California, Santa Clara, CA

4Department of Oncology, Oakland Medical Center, Kaiser Permanente Northern California, Oakland, CA

Corresponding Author

Lisa J Herrinton, PhD ()

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Keywords: acute myeloid leukemia, adverse events, care delivery, community-based studies, health services research, induction chemotherapy

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