You are leaving Medscape Education
Cancel Continue
Log in to save activities Your saved activities will show here so that you can easily access them whenever you're ready. Log in here CME & Education Log in to keep track of your credits.
 

Table 1.  

Characteristic No. % Median (range)
Age at diagnosis, y     64 (60-75)
 60-64 54 51.4  
 65-70 37 35.3  
 71-75 14 13.3  
Sex      
 Male 65 61.9  
 Female 40 38.1  
AML disease type      
 De novo 73 69.5  
 Secondary 32 30.5  
ELN 2017 criteria      
 Favorable 24 22.9  
 Intermediate 49 46.7  
 Poor 32 30.5  
Genetic mutation      
 Biallelic CEBPA 6 5.7  
 NPM1 without FLT3-  ITD or with FLT3-ITD (low) 13 12.4  
 NPM1 with FLT3-ITD  (high) 10 9.5  
 FLT3-ITD (high)  without NPM1 9 8.6  
 RUNX1 10 9.5  
 ASXL1 9 8.6  
 TP53 2 1.9  
Laboratory findings at baseline      
 WBC × 109/L     3.8 (0.3-345.7)
 Hemoglobin     9.1 (5.2-13.0)
 Platelet count × 109/L     68.0 (9.0-827.0)
 Creatinine, mg/dL     0.9 (0.5-1.7)
 Albumin, g/dL     3.8 (2.8-5.0)
 Fibrinogen, mg/dL     344.0 (57.0-500.0)
 Lactate  dehydrogenase, U/L     471.0 (184.0-13 200.0)
Basic assessment      
 Cardiac function,  LVEF (%)     64.0 (52.0-74.2)
 Pulmonary function      
  FEV-1 (%)     88.0 (57.0-115.0)
  Adjusted DLCO (%)     77.0 (42.0-119.0)
 ECOG PS      
  0-1 98 93.3  
  2 7 6.7  
 HCT-CI      
  ≥3 24 22.9  
  ≥4 15 14.3  
  ≥5 9 8.6  
Wheatley index*      
 Score     7 (4-14)
  Good risk (4-6) 52 49.5  
  Standard risk (7-8) 30 28.6  
  Poor risk (≥9) 23 21.9  
AML scores      
 ED score, %     18.9 (6.1-52.4)
  1st quartile 26 24.8  
  2nd quartile 26 24.8  
  3rd quartile 24 22.9  
  4th quartile 29 27.6  
 CR score, %     61.3 (14.5-90.6)
  1st quartile 27 25.7  
  2nd quartile 26 24.8  
  3rd quartile 28 26.7  
  4th quartile 24 22.8  
Ferrara criteria      
 Age 75 years or  older 1    
 ECOG PS ≥3 0    
 Heart (LVEF ≤50%) 0    
 Lungs (DLCO ≤65%  or FEV-1 ≤65%) 21    
 Kidney (on dialysis) 3    
 Liver (LFT >3×  normal values) 4    
 Infection (resistant to  anti-infective therapy) 0    
 Mental illness or  uncontrolled cognitive status 0    
 Any other  comorbidity that the physician judged to be incompatible with chemotherapy 0    
 Unfit‡ 28 26.7  

Table 1. Baseline characteristics of the study cohort (N = 105)

DLCO, diffusing capacity of lungs for carbon monoxide; FEV-1, forced expiratory volume at 1 second; ITD, internal tandem duplication; LFT, liver function test; LVEF, left ventricular ejection fraction; WBC, white blood cell count.

Wheatley risk score comprises cytogenetic risk group, WBC group, ECOG PS, age group, and AML type.16

AML scores calculate the probability of CR or ED (%) with appropriate formula, including initial body temperature, hemoglobin, platelet count, fibrinogen level, lactate dehydrogenase level, age, cytogenetic/molecular risk classification, and AML type.14

Ferrara operation criteria define unfitness for intensive chemotherapy in AML. The definition of unfitness for intensive chemotherapy should require the fulfillment of ≥1 of 9 criteria.44

Table 2.  

GA category Score No. % Median (range)
Physical function assessment
K-MBI as ADL measurement       105 (24-05)
 Impaired K-MBI ≤100 10 9.5  
K-IADL       10 (10-28)
 Impaired K-IADL ≥12 31 29.5  
SPPB       10 (3-12)
 Impaired SPPB ≤8 37 35.2  
  Standing balance consists of 3 subsequent balance tests ≤3 points      
  Side-by-side stand <10 s 0 points 0    
  Semitandem stand <10 s 0 points 3 2.9  
  Tandem stand <10 s   18 17.2  
   3.0-9.9 s 1 point 9 50.0  
   >3.0 s or cannot perform 0 points 9 50.0  
  Gait speed assessment (4   meters), ≥4.82 s        
   <4.82 s 4 points 48 45.7  
   4.82-6.20 s 3 points 27 25.7  
   6.21-8.70 s 2 points 14 13.3  
   >8.70 s 1 point 6 5.7  
   Cannot perform 0 points 10 9.5  
  Sit-and-stand speed, 5 times   (≥11.19 s)        
   <11.19 s 4 points 46 43.8  
   11.19-13.69 s 3 points 21 20.0  
   13.70-16.69 s 2 points 17 16.2  
   >16.7 s 1 point 9 8.6  
   <60 s or cannot perform 0 points 12 11.4  
 Handgrip strength        
  Dominant hand strength, kg       28 (12-46)
   Male       34 (12-46)
   Female       21 (13-28)
  Impaired handgrip strength, dominant hand (≤4th quartile)   24 22.9  
   Male   10    
   Female   14    
Nutritional status assessment
MNA       25.5 (10.5-33.0)
 Impaired MNA ≤23.5 35 33.3  
Social support assessment
OARS       16 (8-24)
 Impaired OARS ≥18 34 32.4  
Cognition function assessment
MMSE-KC       26 (15-30)
 Impaired MMSE-KC ≤23 35 33.3  
  No cognitive impairment 24-30 70 66.7  
  Mild cognitive impairment 18-23 31 29.5  
  Severe cognitive impairment 0-17 4 3.8  
 KNU-DESC       0 (0-3)
  Impaired KNU-DESC ≥2 2 1.9  
Psychological function assessment
SGDS-K       2 (0-15)
 Impaired SGDS-K, moderate depressive symptom ≥6 19 18.1  
  No depression 0-5 86 81.9  
  Moderate depressive symptom 6-9 9 8.6  
  Major depression ≥10 10 9.5  
 PHQ-9       5 (0-27)
  Impaired PHQ-9, mild depression ≥6 50 47.6  
  No depression 0-5 55 52.4  
  Mild depression 6-8 18 17.1  
  Moderate depression 9-14 19 18.1  
  Severe depression ≥15 13 12.4  
 NCCN distress thermometer       3 (0-10)
  Impaired NCCN distress thermometer ≥3 64 61.0  

Table 2. Baseline GA measures for the study cohort (N = 105)

ADL, activity of daily living.

CME / ABIM MOC

Geriatric Assessment Predicts Nonfatal Toxicities and Survival for Intensively Treated Older Adults With AML

  • Authors: Gi-June Min, MD, PhD; Byung-Sik Cho, MD, PhD; Sung-Soo Park, MD, PhD; Silvia Park, MD, PhD; Young-Woo Jeon, MD, PhD; Seung-Hwan Shin, MD, PhD; Seung-Ah Yahng, MD, PhD; Jae-Ho Yoon, MD, PhD; Sung-Eun Lee, MD, PhD; Ki-Seong Eom, MD, PhD; Yoo-Jin Kim, MD, PhD; Seok Lee, MD, PhD; Chang-Ki Min, MD, PhD; Seok-Goo Cho, MD, PhD; Dong-Wook Kim, MD, PhD; Jong Wook Lee, MD, PhD; Hee-Je Kim, MD, PhD
  • CME / ABIM MOC Released: 3/17/2022
  • Valid for credit through: 3/17/2023
Start Activity

  • Credits Available

    Physicians - maximum of 1.00 AMA PRA Category 1 Credit(s)™

    ABIM Diplomates - maximum of 1.00 ABIM MOC points

    You Are Eligible For

    • Letter of Completion
    • ABIM MOC points

Target Audience and Goal Statement

This activity is intended for hematologists, oncologists, internists, geriatricians, and other clinicians caring for older patients (age > 60 years) with acute myeloid leukemia (AML).

The goal of this activity is to describe the prognostic value of multiparameter geriatric assessment (GA) domains on treatment tolerance and outcomes after intensive chemotherapy with cytarabine and idarubicin in 105 newly diagnosed older adults (age > 60 years) with AML, according to a single-institution prospective cohort study.

Upon completion of this activity, participants will:

  1. Describe the prognostic value of geriatric assessment (GA) measures regarding treatment tolerance during induction chemotherapy in newly diagnosed older adults with acute myeloid leukemia (AML), according to a single-institution prospective cohort study
  2. Determine the prognostic value of GA measures regarding survival outcomes after induction chemotherapy in newly diagnosed older adults with AML, according to a single-institution prospective cohort study
  3. Identify improvement of existing survival prediction models by GA measures among newly diagnosed older adults with AML, and other clinical implications of this single-institution prospective cohort study


Disclosures

Medscape, LLC requires every individual in a position to control educational content to disclose all financial relationships with ineligible companies that have occurred within the past 24 months. Ineligible companies are organizations whose primary business is producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients.

All relevant financial relationships for anyone with the ability to control the content of this educational activity are listed below and have been mitigated according to Medscape policies. Others involved in the planning of this activity have no relevant financial relationships.


Faculty

  • Gi-June Min, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Byung-Sik Cho, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Sung-Soo Park, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Silvia Park, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Young-Woo Jeon, MD, PhD

    Department of Hematology
    Yeouido St Mary's Hospital
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Seung-Hwan Shin, MD, PhD

    Department of Hematology
    Eunpyeong St Mary's Hospital
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Seung-Ah Yahng, MD, PhD

    Department of Hematology
    Incheon St Mary's Hospital
    College of Medicine
    The Catholic University of Korea,
    Seoul, Republic of Korea

  • Jae-Ho Yoon, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Sung-Eun Lee, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Ki-Seong Eom, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Yoo-Jin Kim, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Seok Lee, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Chang-Ki Min, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Seok-Goo Cho, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Dong-Wook Kim, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Jong Wook Lee, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

  • Hee-Je Kim, MD, PhD

    Department of Hematology
    Catholic Hematology Hospital
    Seoul St Mary's Hospital
    Leukemia Research Institute
    College of Medicine
    The Catholic University of Korea
    Seoul, Republic of Korea

CME Author

  • Laurie Barclay, MD

    Freelance writer and reviewer
    Medscape, LLC

    Disclosures

    Disclosure: Laurie Barclay, MD, has disclosed the following relevant financial relationships:
    Stock, stock options, or bonds from: AbbVie Inc. (former)

Editor

  • Selina M. Luger, MD

    Associate Editor, Blood

    Disclosures

    Disclosure Selina M. Luger, MD, has disclosed the following relevant financial relationships:
    Research funding from: Celgene Corporation; Kura Oncology, Inc.; Onconova Therapeutics, Inc.
    Consultant or advisor: Bristol-Myers Squibb Company (former); Loxo Oncology (former); Pluristem Therapeutics Inc. (former)

CME Reviewer

  • Leigh A. Schmidt, MSN, RN, CMSRN, CNE, CHCP

    Associate Director, Accreditation and Compliance
    Medscape, LLC

    Disclosures

    Disclosure: Leigh A. Schmidt, MSN, RN, CMSRN, CNE, CHCP, has disclosed no relevant financial relationships.


Accreditation Statements



In support of improving patient care, this activity has been planned and implemented by Medscape, LLC and the American Society of Hematology. Medscape, LLC is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.

    For Physicians

  • Medscape, LLC designates this Journal-based CME activity for a maximum of 1.0  AMA PRA Category 1 Credit(s)™ . Physicians should claim only the credit commensurate with the extent of their participation in the activity.

    Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to 1.0 MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program. Participants will earn MOC points equivalent to the amount of CME credits claimed for the activity. It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting ABIM MOC credit.

    Contact This Provider

For questions regarding the content of this activity, contact the accredited provider for this CME/CE activity noted above. For technical assistance, contact [email protected]


Instructions for Participation and Credit

There are no fees for participating in or receiving credit for this online educational activity. For information on applicability and acceptance of continuing education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity online during the valid credit period that is noted on the title page. To receive AMA PRA Category 1 Credit™, you must receive a minimum score of 70% on the post-test.

Follow these steps to earn CME/CE credit*:

  1. Read about the target audience, learning objectives, and author disclosures.
  2. Study the educational content online or print it out.
  3. Online, choose the best answer to each test question. To receive a certificate, you must receive a passing score as designated at the top of the test. We encourage you to complete the Activity Evaluation to provide feedback for future programming.

You may now view or print the certificate from your CME/CE Tracker. You may print the certificate, but you cannot alter it. Credits will be tallied in your CME/CE Tracker and archived for 6 years; at any point within this time period, you can print out the tally as well as the certificates from the CME/CE Tracker.

*The credit that you receive is based on your user profile.

From Blood
CME / ABIM MOC

Geriatric Assessment Predicts Nonfatal Toxicities and Survival for Intensively Treated Older Adults With AML

Authors: Gi-June Min, MD, PhD; Byung-Sik Cho, MD, PhD; Sung-Soo Park, MD, PhD; Silvia Park, MD, PhD; Young-Woo Jeon, MD, PhD; Seung-Hwan Shin, MD, PhD; Seung-Ah Yahng, MD, PhD; Jae-Ho Yoon, MD, PhD; Sung-Eun Lee, MD, PhD; Ki-Seong Eom, MD, PhD; Yoo-Jin Kim, MD, PhD; Seok Lee, MD, PhD; Chang-Ki Min, MD, PhD; Seok-Goo Cho, MD, PhD; Dong-Wook Kim, MD, PhD; Jong Wook Lee, MD, PhD; Hee-Je Kim, MD, PhDFaculty and Disclosures

CME / ABIM MOC Released: 3/17/2022

Valid for credit through: 3/17/2023

processing....

Abstract and Introduction

Abstract

Given that there are only a few prospective studies with conflicting results, we investigated the prognostic value of multiparameter geriatric assessment (GA) domains on tolerance and outcomes after intensive chemotherapy in older adults with acute myeloid leukemia (AML). In all, 105 newly diagnosed patients with AML who were older than age 60 years and who received intensive chemotherapy consisting of cytarabine and idarubicin were enrolled prospectively. Pretreatment GA included evaluations for social and nutritional support, cognition, depression, distress, and physical function. The median age was 64 years (range, 60-75 years), and 93% had an Eastern Cooperative Oncology Group performance score <2. Between 32.4% and 69.5% of patients met the criteria for impairment for each domain of GA. Physical impairment by the Short Physical Performance Battery (SPPB) and cognitive dysfunction by the Mini-Mental State Examination in the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Assessment Packet (MMSE-KC) were significantly associated with nonfatal toxicities, including grade 3 to 4 infections (SPPB, P = .024; MMSE-KC, P = .044), acute renal failure (SPPB, P = .013), and/or prolonged hospitalization (≥40 days) during induction chemotherapy (MMSE-KC, P = .005). Reduced physical function by SPPB and depressive symptoms by the Korean version of the short form of geriatric depression scales (SGDS-K) were significantly associated with inferior survival (SPPB, P = .027; SGDS-K, P = .048). Gait speed and sit-and-stand speed were the most powerful measurements for predicting survival outcomes. Notably, the addition of SPPB and SGDS-K, gait speed and SGDS-K, or sit-and-stand speed and SGDS-K significantly improved the power of existing survival prediction models. In conclusion, GA improved risk stratification for treatment decisions and may inform interventions to improve outcomes for older adults with AML. This study was registered at the Clinical Research Information Service as #KCT0002172.

Introduction

Acute myeloid leukemia (AML) is a disease of the elderly with a median age at diagnosis between 68 and 72 years.[1,2] Older adults with AML (usually defined as age ≥60) have worse survival outcomes than younger patients with AML because they have different biology and more frequently have unfavorable cytogenetics, a decline in performance status, and acquired comorbidities.[3] The mutational spectrum in older adults with AML also differs from that in younger patients,[4] and differentiated mutational patterns could aid precise prognostication.[5] Selected cases of older adults with AML can benefit from intensive chemotherapy, including that containing anthracycline and cytarabine, despite the risk for increased toxicity from treatment.[3,6,7] Several prognostic models have been developed to identify patients at high risk of early death (ED), treatment resistance, or poor survival after conventional intensive AML therapy.[8] However, they were limited by low accuracy and the need for reassessment to reflect changes resulting from continuous improvement in supportive care.[8]

Chronological age, performance status, and comorbidities are commonly used to determine fitness for intensive treatment. These variables are relatively easy to assess but are limited in capturing the heterogeneity of older patients with hematologic malignancies.[9-11] Therefore, additional assessment tools are needed to better characterize fitness in the context of therapy and to capture the frailty that arises from “decreased reserves in multiple organ systems, which are initiated by disease, lack of activity, inadequate nutritional intake, stress, and/or the physiologic changes by aging.”[10,11] Among various frailty assessments, multiparameter geriatric assessment (GA) offers more comprehensive evaluations, including functional ability, physical health, cognition, psychological health, nutritional status, and social support.[10,11] Despite the growing evidence that GA can detect unrecognized vulnerabilities in patients with hematologic malignancies to help predict treatment tolerance and survival, GA is limited by lack of standardization and consensus regarding its prognostic value in older adults with AML.[10,11] Two previous prospective studies of GA in older adults with AML had conflicting results regarding the role of physical performance measures as survival predictors, suggesting the need for further prospective validation of GAs.[12,13] Furthermore, the degree to which preexisting survival prediction models, such as web-based prediction models for AML (AML scores),[14] Ferrara criteria,[15] or Wheatley index,[16] can be improved by integrating components of GA still needs to be determined.[8] Here, we report the results of a single-institution prospective cohort study that included newly diagnosed older adults with AML who received homogeneous intensive induction chemotherapy to determine which patient-related characteristics assessed by GA predict treatment tolerance and outcomes and how much they can improve survival prediction tools.