Background

Morbidity and mortality in tumor lysis syndrome (TLS) remains high despite increasing efforts for prevention, early detection and treatment in recent years. The current risk stratification system and treatment guidelines are largely consensus based without strong evidence. There is paucity of data on the in-hospital mortality and predictors of poor clinical outcome in this population.

Methods

We used the 2009-2011 Nationwide Inpatient Sample database to identify hospitalizations in patients ≥18 years with a diagnosis of TLS (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] code 277.88). Nationwide Inpatient Sample is the largest all-payer publicly available inpatient care database in the US. It contains data from five to eight million hospital stays from about 1,000 hospitals across the country and approximates a 20% sample of all US hospitals. The interval 2009-2011 was selected as ICD-9-CM code 277.88 for TLS was only introduced from the year 2009 onwards. Univariate and multivariate logistic regression were used to determine the independent predictors of in-hospital mortality. Data analysis was done using STATA version 13.0 (College Station, TX).

Results

Among the 997 admissions (mean age ± SD 67.58±3.33, 62.6 % males, and 80.4 % white) with TLS, in-hospital mortality was 14.44 %. Based on the results of univariate analyses (table 1), we used obesity, coronary artery disease, cardiac dysrhythmias, acute kidney injury and sepsis in the final regression model. We found that cardiac dysrhythmias (OR 4.79; 95% CI, 1.67-13.77; p=0.004) and sepsis (OR 19.70; 95% CI, 5.33-72.78; p<0.001) were independent predictors of increased in-hospital mortality in patients with TLS. Although certain myeloid and lymphoid malignancies are associated with higher risk of tumor lysis syndrome, we did not observe any statistically significant increased risk of mortality with one specific type of malignancy over the other. Similarly, none of the demographic characteristics (age <40 vs ≥40, sex or race), or hospital characteristics (rural vs urban, teaching vs non-teaching, small vs large bed-size or geographic region) predicted increased in-hospital mortality in these patients.

Conclusion

In this study of large national database, patients with TLS had an in-hospital mortality of 14.44 %. Independent predictors of in-hospital mortality were cardiac dysrhythmias and sepsis. Our findings might help physicians to identify sub-group of patients with TLS that are at increased risk of in-hospital mortality.

Table 1

Baseline characteristics of patients with tumor lysis syndrome according to in-hospital survival

Characteristics Survivors (n=853)Non-survivors (n=144)p
Age( in years) Mean 68.40±3.06 67.58±3.33 0.73 
Male sex  62.1 65.8 0.69 
Race    0.16 
 White 81.52 73.54  
 Black 14.98 22.8  
 Hispanic 2.27 0  
 Others/unknown 1.22 3.66  
Insurance status    0.41 
 Medicare 65.55 48.15  
 Medicaid 5.56 13.34  
 Private insurance 24.89 32.58  
 Self-Pay 0.65 2.99  
 No charge 0.63 0  
 Other 2.72 2.93  
Region    0.13 
 Northeast 27.59 37.74  
 Midwest 28.23 12.92  
 South 31.34 39.9  
 West 12.84 9.44  
Location/teaching status   0.59 
 Rural 7.87 10.16  
 Urban nonteaching 26.01 33.52  
 Urban teaching 66.12 56.32  
Bed-size    0.84 
 Small 11.11 8.91  
 Medium 21.04 24.55  
 Large 67.85 66.54  
Malignancies     
 ALL 1.19 6.79 0.25 
 AML 2.34 6.99 0.29 
 CLL 27.86 16.83 0.18 
 CML 1.85 3.19 0.68 
 NHL 36.33 22.37 0.1 
 HD 0.53 0 0.32 
 Multiple Myeloma 7.39 6.56 0.82 
 Other hematologic malignancies 38.67 25.99 0.16 
 Solid tumors 35.87 26.8 0.32 
Co-morbidities     
 Smoking 15.89 21.87 0.46 
 Obesity 5.16 0 0.005 
 Dyslipidemia 27.8 16.86 0.18 
 Hypertension 54.17 49.19 0.63 
 Diabetes mellitus 27.81 16.65 0.15 
 PVD 1.71 3.19 0.65 
 CAD 13.78 3.19 0.02 
 AKI 60.06 79.54 0.03 
 CKD 28.81 25.23 0.65 
 Stroke 0.63 0 0.32 
 Sepsis 3.58 31.81 0.003 
 Cardiac dysrhythmias 17.96 43.42 0.04 
 Acute CHF 11.44 7.08 0.43 
Characteristics Survivors (n=853)Non-survivors (n=144)p
Age( in years) Mean 68.40±3.06 67.58±3.33 0.73 
Male sex  62.1 65.8 0.69 
Race    0.16 
 White 81.52 73.54  
 Black 14.98 22.8  
 Hispanic 2.27 0  
 Others/unknown 1.22 3.66  
Insurance status    0.41 
 Medicare 65.55 48.15  
 Medicaid 5.56 13.34  
 Private insurance 24.89 32.58  
 Self-Pay 0.65 2.99  
 No charge 0.63 0  
 Other 2.72 2.93  
Region    0.13 
 Northeast 27.59 37.74  
 Midwest 28.23 12.92  
 South 31.34 39.9  
 West 12.84 9.44  
Location/teaching status   0.59 
 Rural 7.87 10.16  
 Urban nonteaching 26.01 33.52  
 Urban teaching 66.12 56.32  
Bed-size    0.84 
 Small 11.11 8.91  
 Medium 21.04 24.55  
 Large 67.85 66.54  
Malignancies     
 ALL 1.19 6.79 0.25 
 AML 2.34 6.99 0.29 
 CLL 27.86 16.83 0.18 
 CML 1.85 3.19 0.68 
 NHL 36.33 22.37 0.1 
 HD 0.53 0 0.32 
 Multiple Myeloma 7.39 6.56 0.82 
 Other hematologic malignancies 38.67 25.99 0.16 
 Solid tumors 35.87 26.8 0.32 
Co-morbidities     
 Smoking 15.89 21.87 0.46 
 Obesity 5.16 0 0.005 
 Dyslipidemia 27.8 16.86 0.18 
 Hypertension 54.17 49.19 0.63 
 Diabetes mellitus 27.81 16.65 0.15 
 PVD 1.71 3.19 0.65 
 CAD 13.78 3.19 0.02 
 AKI 60.06 79.54 0.03 
 CKD 28.81 25.23 0.65 
 Stroke 0.63 0 0.32 
 Sepsis 3.58 31.81 0.003 
 Cardiac dysrhythmias 17.96 43.42 0.04 
 Acute CHF 11.44 7.08 0.43 
View Large

AKI=Acute Kidney Injury; ALL=Acute Lymphoblastic Leukemia; AML=Acute Myelogenous Leukemia; CAD=Coronary Artery Disease; CHF=Congestive Heart Failure; CKD=Chronic Kidney Disease; CLL=Chronic Lymphocytic Leukemia; CML=Chronic Myelogenous Leukemia; HD=Hodgkin Disease; NHL=Non Hodgkin Lymphoma; PVD=Peripheral Vascular Disease

Disclosures

No relevant conflicts of interest to declare.

Topics:
hospital mortality, tumor lysis syndrome, obesity, cardiac arrhythmia, sepsis, cancer, leukemia, myeloid, lymphoblastic leukemia, arterial disease, cerebrovascular accident

Author notes

*

Asterisk with author names denotes non-ASH members.

© 2014 by The American Society of Hematology
2014
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