1. TREATMENT AND LONG-TERM COSTS OF PEDIATRIC ACUTE
LYMPHOBLASTIC LEUKEMIA
9th ANNUAL UTAH HEALTH SERVICES RESEARCH CONFERENCE
April 30th, 2014
Sapna Kaul, PhD, MA
Post-Doctoral Research Associate, Health Economics
Hematology/Oncology, Department of Pediatrics

2. INTRODUCTION

3. INTRODUCTION
• Why study pediatric cancer costs?
• Assess economic burden over time
• Cost effectiveness analyses
• Cost benefit analyses
• Cost containment techniques
• Costs of pediatric cancer is an understudies area.
• HCUP’s study on pediatric cancer hospitalizations, 2009.
• Russell et al. (2012, Pediatrics)
Systematic review of economic evaluations of pediatric cancer treatments.
Majority of the studies were by European investigators. Only 10 studies by U.S.
investigators.
Approaches to Value Based Care

4. WHY ACUTE LYMPHOBLASTIC LEUKEMIA (ALL)?
• Accounts for 25% to 30% of childhood cancer diagnoses.
• About 3,000 children and adolescents are diagnosed with ALL every year in the U.S.
• The incidence rate has gradually increased over time and survival rate 85% to 90%.
• Survival rates in Black and Hispanic children are lower than White children with ALL.
Blood Stem Cell
Lymphoid B Lymphocyte
T Lymphocyte
Myeloid

5. ALL TREATMENT
Induction
35 days
Post-Induction
Standard Risk = 9 months
High Risk = 7 months
Maintenance
Girls = 2 years
Boys= 3 years
Long-Term
> 5 years
Vary by risk and sex …
Standard risk – WBC count less than 50,000/μL and age 1 to younger than 10 years.
High risk – WBC count 50,000/μL or greater and/or age 10 years or older.

6. OBJECTIVES
• Examine hospitalizations costs of pediatric ALL over time.
- Aggregate costs.
- Disaggregate costs by cost components (room & care, diagnostics etc.) and
treatment phases (induction, post-induction, maintenance, long-term).
• Investigate factors that affect hospitalization costs.
‐ Treatment related factors (risk, relapse, infections etc.).
‐ Socio-economic factors (insurance, distance from hospital).

7. DATA
• N=553 pediatric ALL patients.
• Patients identified through the Intermountain Healthcare System.
• Diagnosed years 1998 to 2013.
• Longitudinal data – hospitalizations data with costs.
• Cost data adjusted for inflation using Consumer Price Index.

8. STATISTICAL METHODS
• Aggregate and disaggregate costs
-Annual average per patient hospitalization costs.
-Annual average costs by cost components and treatment phases.
• Factors that affect per patient hospitalization costs
- Multivariable regression – GLM.
- Separate regressions – within and after 5 years of diagnosis.
Analyses in STATA and R …..

9. Characteristics N %
Age at Diagnosis
(years)
< 1
1- 5
5 - 10
>10
19
306
100
128
3
55
18
23
Sex Female
Male
263
290
48
52
Race White
Non-White
484
69
87
12
Insurance at Diagnosis Public
Private
Uninsured
133
399
21
24
72
4
Residence at ALL Diagnosis UT
AZ, CO, ID, MT, NV,
WY
AK, CA, MO, WA
441
105
7
80
19
1
Patients Characteristics

10. Treatment Related Characteristics
ALL Specific Characteristics N %
ALL Risk
Infants
Standard Risk
High Risk
19
343
191
3
62
34
Phases for Standard and High Risk Patients
Induction
Post-Induction
Maintenance
Long-Term
521
376
337
99
97
72
60
19
ALL Relapse
Yes
No
63
490
11
89
Transplant
Yes
No
45
508
8
92
Mortality
Alive
Dead
490
63
89
11
- 97% patients were
diagnosed at Primary
Children’s Hospital
- Annual diagnoses
varied from 25 to 40
from 1998 to 2013

11. RESULTS
Aggregate Costs
2000 2005 2010
051015
Per Patient Per Hospitalization Average Annual Costs
Years
AverageCostsin$1000
Average Costs Per Hospitalization among ALL Patients

12. Disaggregated Costs by Cost Components
2000 2005 2010
02468
Per Patient Per Hospitalization Average Annual Costs
Years
AverageCostsin$1000
Room & Care
Therapy
Pharmacy
Diagnostic
Average Costs Per Hospitalization among ALL Patients

13. Disaggregated Costs by Treatment Phases
2000 2005 2010
05101520
Per Patient Per Hospitalization Average Annual Costs
Years
AverageCostsin$1000
Induction
Post-Induction
Maintenance
Long-Term
Average Costs Per Hospitalization among ALL Patients

14. Multivariable Regression Analysis for Treatment Costs within 5 years of Diagnosis
N=424, Hospitalizations=2887
Independent Variables Effect on Dependent
Variable
P-value
Treatment Related Characteristics
High Risk vs. Standard Risk 2298 <0.01
Relapse vs. no Relapse 3302 <0.01
Induction vs. Post-Induction 7160 <0.01
Infection vs. no Infection 1916 <0.05
Socio-Demographic Characteristics
Public vs. Private Insurance 1274 <0.01
Insignificant variables – race, sex, distance from facility etc. Controlled for fixed year effects.
Exclusions – infants, residents of WA, AK, MO, CA, and diagnosis after 2010.

15. Variable Effect on Dependent
Variable
P-value
Treatment Related Characteristics
Relapse vs. no Relapse 4355 <0.01
Infection vs. no
Infection
9884 <0.05
Socio-Demographic Characteristics
Uninsured vs. Private -3827 <0.05
N=99, Hospitalizations=237
Multivariable Regression Analysis for Long-Term Costs Starting 5 years after Diagnosis
The remaining variables were insignificant.
Exclusions – Residents of WA, AK, MO, CA.

16. CONCLUSIONS
• Average cost per hospitalization has increased over time. Increase differs
substantially by cost components and treatment phases.
• Factors that potentially increase costs:
• Treatment related and socio-demographic characteristics.
• Costs of treating infants very high – upper limit of $151,167 per visit.
• Value based care:
• Cost-effective patient-centered care for High Risk and Relapsed patients.
• Emphasis on managing induction, room and care, and pharmacy costs.
• Insurance can provide leads on monitoring high cost patients.

17. LIMITATIONS
Economic
Burden of
Pediatric
ALL
Hospitalization
Costs
Other Medical Costs
e.g. Physician Costs,
Outpatient Costs
Indirect Medical
Costs

18. NEXT STEPS
• Use more refined treatment phase identifiers (e.g., LPs and pharmacy data).
• Incorporate physician costs and out-patient medical costs.
• Robust examination of late effects include patients diagnosed in 1980’s.
• Costs of all Pediatric cancers.

19. COLLABORATORS AND FUNDING
Anne C. Kirchhoff, PhD, MPH
Richard Lemons, MD
Kent Korgenski, MS
Mark Fluchel, MD
Anupam Verma, MD
Elizabeth Raetz, MD
Richard Nelson, PhD
Josh Schiffman, MD
Christi Ng, MPH
Seth Andrews, MBA
Funding Source: Primary Children’s Hospital’s Pediatric Cancer Program (PCHPCP)

20. OUTLINE
• Introduction
• Objectives
• Data and Statistical Methods
• Results
• Conclusions
• Limitations and Next Steps