Abstract

Introduction

Myeloma patients that experience a pathological fracture have 44% increased risk of mortality compared to their counterparts without pathological fractures. Given the negative impact of pathological fractures on survival, we have explored if access to obtain a therapeutic procedure influences the survival. We analyzed the nationwide inpatient cohort to evaluate for access to procedures and other hospitalization variables for myeloma patients admitted to the hospital for the diagnosis of pathologic fractures.

Methodology

Myeloma patients admitted in the hospital for the primary diagnosis of pathologic fractures from 2001-2010 were analyzed from the Nationwide Inpatient Sample (NIS). Procedures and diagnoses were identified using ICD-9-CM and NIS CCS codes. Variables of therapeutic procedures, length of stay (LOS), in-hospital mortality (IHM) and hospital charges were explored using multivariate logistic regression. Costs are derived from total hospital charges using cost-to-charge ratios based on hospital accounting reports from the Centers for Medicare and Medicaid Services and reflect the actual costs to produce hospital services.

Results

Of the 5154 myeloma patient admitted for pathological fractures, 2422 patients (47%) underwent a therapeutic procedure. The mean LOS for the primary diagnosis was 7.23 days (SE 0.14); cost for the hospitalization was $19344 and the IHM is 2.32%. The probability of getting a therapeutic surgical procedure and the cost of hospitalization is lower in patients >65, but had similar LOS and IHM compared to patients <65. Similar probability of not getting a surgical procedure was seen in medicare patients; but longer LOS may have contributed to the similar cost. However, in the medicaid patients, the odds of getting a surgical procedure was 66% low; the LOS and the cost are significantly high compared to the private insurance. IHM did not differ significantly across all groups.

Conclusions

This analysis addresses the question that older myeloma patients (age >65) and those that have the payer status of medicare and medicaid are significantly associated with the probability of not getting a therapeutic surgical procedure when they are admitted with pathological fracture. However, this did not result in increased in-hospital mortality suggesting that probably pathological fractures may reflect the biology of the underlying disease with negative impact on survival or the morbidity associated with a pathological fracture may impede the long term survival in myeloma patients.

Table 1

Multivariate model of outcome analysis in myeloma patients with pathologic fractures

VariableProbability of not getting procedureLength of stay > 7 dCost > $19,344In-hospital Mortality
Odds Ratio (95% CI)p-valueOdds Ratio
(95% CI)
p-valueOdds Ratio
(95% CI)
p-valueOdds Ratio
(95% CI)
p-value
Age 
>65 years 1.00 (ref)  1.00 (ref)  1.00 (ref)  1.00 (ref)  
< 65 years 0.708 (0.587-0.856) 0.0003 0.964 (0.789-1.177) 0.716 1.389 (1.114-1.732) 0.0035 0.656 (0.321-1.339) 0.2468 
Sex 
Female 1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  1.00 (ref)  
Male 1.001 (0.885-1.131) 0.989 0.933 (0.812-1.072) 0.3289 1.032 (0.892-1.196) 0.6697 1.289 (0.828-2.008) 0.2613 
Race 
White 1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  1.00 (ref)  
Black 1.025 (0.850-1.236) 0.69 1.689 (1.409-2.025 0.0011 1.166 (0.946-1.437) 0.7268 1.314 (0.773-2.233) 0.2553 
Others 1.139 (0.905-1.433) 0.316 1.376 (1.107-1.709) 0.6033 1.260 (0.995-1.597) 0.1927 0.874 (0.409-1.867) 0.4791 
Payer status 
Private Insurance 1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  
Medicare 1.390 (1.138-1.698) 0.370 1.218 (0.986-1.506) 0.1302 1.123 (0.899-1.402) 0.5462 1.24 (0.585-2.627) 0.5505 
Medicaid 1.600 (1.169-2.188) 0.074 2.123 (1.53-2.945) 0.0004 1.711 (1.231-2.380) 0.0044 2.002 (0.794-5.047) 0.0865 
VariableProbability of not getting procedureLength of stay > 7 dCost > $19,344In-hospital Mortality
Odds Ratio (95% CI)p-valueOdds Ratio
(95% CI)
p-valueOdds Ratio
(95% CI)
p-valueOdds Ratio
(95% CI)
p-value
Age 
>65 years 1.00 (ref)  1.00 (ref)  1.00 (ref)  1.00 (ref)  
< 65 years 0.708 (0.587-0.856) 0.0003 0.964 (0.789-1.177) 0.716 1.389 (1.114-1.732) 0.0035 0.656 (0.321-1.339) 0.2468 
Sex 
Female 1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  1.00 (ref)  
Male 1.001 (0.885-1.131) 0.989 0.933 (0.812-1.072) 0.3289 1.032 (0.892-1.196) 0.6697 1.289 (0.828-2.008) 0.2613 
Race 
White 1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  1.00 (ref)  
Black 1.025 (0.850-1.236) 0.69 1.689 (1.409-2.025 0.0011 1.166 (0.946-1.437) 0.7268 1.314 (0.773-2.233) 0.2553 
Others 1.139 (0.905-1.433) 0.316 1.376 (1.107-1.709) 0.6033 1.260 (0.995-1.597) 0.1927 0.874 (0.409-1.867) 0.4791 
Payer status 
Private Insurance 1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  1.00 (Ref)  
Medicare 1.390 (1.138-1.698) 0.370 1.218 (0.986-1.506) 0.1302 1.123 (0.899-1.402) 0.5462 1.24 (0.585-2.627) 0.5505 
Medicaid 1.600 (1.169-2.188) 0.074 2.123 (1.53-2.945) 0.0004 1.711 (1.231-2.380) 0.0044 2.002 (0.794-5.047) 0.0865 
Disclosures:

Lonial:Millennium: Consultancy; Celgene: Consultancy; Novartis: Consultancy; BMS: Consultancy; Sanofi: Consultancy; Onyx: Consultancy.

Author notes

*

Asterisk with author names denotes non-ASH members.