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Volume 9, Issue 4, July-August 2011, Pages 149-155
Original research
Amit Lahoti MDa,
Background
Acute kidney injury (AKI) is a common complication in critically ill patients with cancer. The RIFLE criteria define three levels of AKI based on the percent increase in serum creatinine (Scr) from baseline: risk (≥50%), injury (≥100%), and failure (≥200% or requiring dialysis). The utility of the RIFLE criteria in critically ill patients with cancer is not known.
Objective
To examine the incidence, outcomes, and costs associated with AKI in critically ill patients with cancer.
Methods
We retrospectively analyzed all patients admitted to a single-center ICU over a 13-month period with a baseline Scr ≤1.5 mg/dL (n = 2,398). Kaplan-Meier estimates for survival by RIFLE category were calculated. Logistic regression was used to determine the association of AKI on 60-day mortality. A log-linear regression model was used for economic analysis. Costs were assessed by hospital charges from the provider's perspective.
Results
For the risk, injury, and failure categories of AKI, incidence rates were 6%, 2.8%, and 3.7%; 60-day survival estimates were 62%, 45%, and 14%; and adjusted odds ratios for 60-day mortality were 2.3, 3, and 14.3, respectively (P ≤ 0.001 compared to patients without AKI). Hematologic malignancy and hematopoietic cell transplant were not associated with mortality in the adjusted analysis. Hospital cost increased by 0.16% per 1% increase in creatinine and by 21% for patients requiring dialysis.
Limitations
Retrospective analysis. Single-center study. No adjustment by cost-to-charge ratios.
Conclusions
AKI is associated with higher mortality and costs in critically ill patients with cancer.
Over the past several years, important advances have occurred in the treatment and supportive care of critically ill patients with cancer.[1] However, acute kidney injury (AKI) remains a familiar complication and is a negative prognostic factor for overall survival.[2] and [3] The development of AKI can limit further cancer treatment, increase toxicity of chemotherapy and reduce its delivery, and exclude patients from clinical trials. Further, patients with AKI have been shown to have longer hospitalizations and increased hospital costs.[4] and [5] Recognized causes of AKI include acute tubular necrosis from medications or sepsis, volume depletion, tumor lysis syndrome, abdominal compartment syndrome, and obstruction from tumor or lymphadenopathy. Elevations in serum creatinine of as little as 0.3 mg/dL, which were previously considered insignificant, have been associated with a higher mortality rate in hospitalized patients.[4] However, few of the numerous definitions of AKI used in the cancer literature incorporate these subtle declines in kidney function.
An increase in serum creatinine has traditionally been used as a reflection of AKI. However, it is well known that elevation in serum creatinine is a relatively late marker of kidney injury.[6] In addition, patients with cancer often have decreased creatinine production secondary to cachexia, which may limit the sensitivity of creatinine as a marker of kidney injury. Other variables including total body volume, ethnicity, medications, and protein intake may also vary the serum creatinine level independent of renal function. Recent studies have demonstrated that a significant number of patients with cancer and normal serum creatinine have underlying chronic kidney disease (CKD) when renal function is estimated by the Cockcroft-Gault equation.[7] and [8] Therefore, using an arbitrarily defined level of serum creatinine as an indicator of AKI (i.e. >1.5 or 2.0 mg/dL) may not be suitable.
What may be a more accurate measure of kidney injury is a classification system based on the percent increase in serum creatinine relative to baseline. One such model is the Risk, Injury, Failure, Loss, and End-Stage Kidney (RIFLE) classification, which defines three levels of severity of AKI (risk, injury, and failure).[9] Previously, over 35 different definitions of AKI were used in the literature, which has made cross-comparisons between studies difficult.[10] The RIFLE classification provides a uniform definition of AKI and has been validated in numerous studies.[11], [12], [13], [14], [15], [16], [17] and [18] The aim of this analysis was to estimate the incidence, outcomes, and costs associated with AKI as defined by the RIFLE classification in critically ill patients with cancer.
Materials and Methods
The study included all patients ≥18 years of age who were admitted to the intensive care unit (ICU) at the University of Texas M.D. Anderson Cancer Center from December 2005 through December 2006. Patients with a baseline serum creatinine >1.5 mg/dL were excluded from the analysis. The protocol was approved by the institutional review board. Demographic and clinical data were obtained from the Department of Critical Care database, the Department of Pharmacy database, and the global institutional database (Enterprise Information Warehouse). The data were incorporated into a single spreadsheet using Excel 12.2 for Mac (Microsoft, Redmond, WA).
RIFLE categories for AKI were defined by the percent increase in serum creatinine from the time of ICU admission to the maximum creatinine at any point during the ICU stay: risk (≥50% rise in serum creatinine), injury (≥100% rise in serum creatinine), and failure (≥200% rise in serum creatinine). Consistent with the Acute Kidney Injury Network modifications of the original criteria, patients who required dialysis were classified into the RIFLE failure category, irrespective of the percent rise in serum creatinine.[19] The modality for continuous renal replacement therapy used at our institution is continuous slow low-efficiency dialysis (c-SLED), which has been described previously.[20] For patients who did not have an initial creatinine available within 24 hours after ICU admission, the most recent prior creatinine within the previous 48 hours was used.
Statistics
Descriptive data are presented as medians with interquartile ranges for continuous variables and absolute numbers with percentages for categorical variables. Survival of patients with AKI as defined by the RIFLE criteria was estimated by the Kaplan-Meier method. Patients were censored at death or last known follow-up, as determined by the clinical record. Statistical significance was determined by the log-rank test.
The primary end point for logistic regression was death at 60 days after ICU admission. Two separate models were developed, examining AKI as a categorical variable (RIFLE categories) and as a continuous variable (percent increase in creatinine from baseline). The variable “age” was significantly associated in a linear fashion with log odds of death but was dichotomized to provide a more meaningful odds ratio for the reader. Correlated data were assessed by correlation coefficients, and no variables were significantly correlated >0.6. Model reduction was achieved by variable elimination using the likelihood ratio test between nested models. Predictive ability and goodness-of-fit statistics were calculated, and the model was internally validated. No significant interactions were identified in either logistic regression model.
Lastly, a multivariate log linear regression model was developed to assess the relationship of AKI and dialysis with hospital cost. Cost was defined as hospital charges from the provider perspective. Log transformation of “cost” was used to account for skewness and heteroskedasticity. Coefficients in this model were multiplied by a factor of 100 to estimate a percent change in the dependent variable (cost) associated with a unit change in the independent variable.[21]
A two-tailed P < 0.05 was considered statistically significant. No patients were excluded from the analysis because of missing data. Statistical analysis was performed with Stata 10 for Mac (StataCorp, College Station, TX).
Results
The data set included 2,398 patients. Patient characteristics are listed in Table 1. The median age was 59 years. The cohort was predominantly Caucasian (75%) and relatively balanced with respect to gender. The majority of patients on a medical service were admitted to the hospital from the emergency room (76%), compared to only 10% of patients on a surgical service. Sepsis was diagnosed in 23% of patients on a medical service vs. only 4% of patients on a surgical service. This is consistent with the large number of patients at our institution who were admitted to the ICU for routine monitoring after elective surgeries. A significant number of patients had underlying hypertension and diabetes (54% and 18%, respectively). One-third of patients had advanced malignancy by Surveillance, Epidemiology, and End Results (SEER) stage on initial presentation to our institution.
b Included if patient received therapy at any time from ICU admission to date of maximum creatinine.
The absolute number of patients developing AKI or requiring dialysis by hospital service is depicted in Figure 1. The incidence of AKI was higher among patients on a medical vs. a surgical service (21% vs. 6.6%). Patients with hematologic malignancies (leukemia, lymphoma, and myeloma) had the highest incidence of AKI and need for dialysis (28% and 9.3%, respectively). Among patients on a medical service, the odds for developing AKI or requiring dialysis were increased 1.9-fold and 5.4-fold, respectively, for patients with an underlying hematologic malignancy.
Figure 1.
Number of Patients with AKI or Needing Dialysis by Hospital Service
AKI, defined as a minimum 50% increase in serum creatinine from baseline, occurred in 301 patients (12.6%), of whom 56 (2.3%) required dialysis. By further defining AKI by the RIFLE criteria, we classified 6%, 3%, and 4% of patients into the RIFLE risk, injury, and failure categories, respectively. The median elevations in creatinine from baseline were 0.6, 1.1, and 2 mg/dL, respectively. The median time to maximum creatinine was two days for all patients with AKI. There was a stepwise decrease in estimated survival associated with each RIFLE category (Figure 2). Among patients in the RIFLE failure group, the estimated survival was similar between those who required dialysis and those who did not (P = 0.99, log-rank). Although survival for patients requiring dialysis was dismal overall, it was significantly worse for patients with underlying hematological malignancy vs. solid tumor (3% vs. 20%, respectively).
The results of the logistic regression model for predictors of death at 60 days after ICU admission is presented in Table 2. Race and gender were not significant on univariate or multivariate analyses. Although significant on univariate analysis, hematologic malignancy, prior hematopoietic cell transplant (HCT), baseline comorbidities (hypertension, diabetes, heart failure, liver disease), and sepsis were also eliminated during model reduction. After adjusting for the remaining covariates, the RIFLE risk, injury, and failure categories remained significantly associated with 60-day mortality with odds ratios of 2.3, 3.0, and 14, respectively.
| VARIABLE | UNIVARIATE | MULTIVARIATE | |||
|---|---|---|---|---|---|
| OR | P | OR | 95% CI | P | |
| Age ≥55 years | 1.2 | 0.08 | 1.5 | 1.1–1.9 | 0.007 |
| Male vs. female | 0.997 | 0.98 | |||
| Ethnicity | |||||
| Black vs. white | 2.0 | <0.001 | |||
| Hispanic vs. white | 1.1 | 0.39 | |||
| Other vs. white | 0.8 | 0.46 | |||
| Hypertension | 1.3 | 0.02 | |||
| Diabetes | 1.6 | <0.001 | |||
| Heart failure | 2.5 | <0.001 | |||
| Chronic liver disease | 1.8 | 0.02 | |||
| RIFLE category | |||||
| Risk vs. no AKI | 4.1 | <0.001 | 2.3 | 1.5–3.6 | <0.001 |
| Injury vs. no AKI | 8.1 | <0.001 | 3.0 | 1.6–5.8 | 0.001 |
| Failure vs. no AKI | 35 | <0.001 | 14.3 | 7.2–29.0 | <0.001 |
| Amphotericin | 10.9 | <0.001 | 1.9 | 1.1–3.3 | 0.03 |
| Vasopressors | 6.3 | <0.001 | 2.0 | 1.4–2.6 | <0.001 |
| Mechanical ventilation | 2.1 | <0.001 | 1.9 | 1.4–2.5 | <0.001 |
| IV diuretics | 3.8 | <0.001 | 1.4 | 1.1–1.9 | 0.015 |
| Sepsis | 5.7 | <0.001 | |||
| Medical vs. surgical service | 9.9 | <0.001 | 2.2 | 1.5–3.1 | <0.001 |
| Liquid vs. solid tumor | 5.5 | <0.001 | |||
| Prior HCT | |||||
| Autologous | 1.7 | 0.23 | |||
| Allogeneic | 6.0 | <0.001 | |||
| Advanced vs. locoregional stage (SEER) | 4.4 | <0.001 | 2.1 | 1.6–2.6 | <0.001 |
| ER admission | 11.3 | <0.001 | 5.3 | 3.7–7.6 | <0.001 |
| Pre-ICU length of stay | 1.06 | <0.001 | 1.02 | 1.0–1.03 | 0.02 |
Likelihood ratio x2(12) = 818 (P < 0.001), positive predictive value 72%, negative predictive value 88%; area under the receiver operating curve = 0.88, Hosmer-Lemeshow x2(8) = 6.8 (P = 0.56).
OR, odds ratio; AKI, acute kidney injury; HCT, hematopoietic cell transplant; ER, emergency room; ICU, intensive care unit.
To further assess the relationship between serum creatinine and mortality, a separate logistic regression was performed using “percent rise in creatinine” as a continuous predictor variable (Table 3). Need for dialysis was also included as an independent variable. Aside from “percent rise in creatinine” and dialysis, model reduction yielded the same covariates as in the initial model. Dialysis had the largest effect on the odds of 60-day mortality (odds ratio = 6.2). After adjusting for dialysis, “percent rise in creatinine” remained significantly associated with 60-day mortality. For example, a 10% rise in creatinine increased the odds of mortality by 8%. The predictive capabilities of both logistic regression models were similar.
| VARIABLE | OR | 95% CI | P |
|---|---|---|---|
| Age ≥55 years | 1.4 | 1.1–1.9 | <0.001 |
| Percent increase in creatinine | 1.008 | 1.005–1.01 | <0.001 |
| ER admission | 5.4 | 3.8–7.7 | <0.001 |
| Pre-ICU length of stay (days) | 1.02 | 1.00–1.04 | 0.016 |
| SEER stage (distant vs. other) | 2.0 | 1.6–2.7 | <0.001 |
| Medical vs. surgical service | 2.2 | 1.5–3.2 | <0.001 |
| Vasopressors | 2.0 | 1.5–2.7 | <0.001 |
| Mechanical ventilation | 1.8 | 1.4–2.5 | <0.001 |
| Amphotericin | 1.8 | 1.1–3.2 | 0.031 |
| IV diuretics | 1.4 | 1.0–1.8 | 0.024 |
| Dialysis | 6.2 | 2.3–16.5 | <0.001 |
Likelihood ratio x2(11) = 815 (P < 0.001), positive predictive value 72%, negative predictive value 88%, area under the receiver operating curve = 0.88.
OR, odds ratio; ICU, intensive care unit; AKI, acute kidney injury; ER, emergency room.
We included AKI as a continuous variable in a multivariate regression to determine the relationship of AKI and dialysis with hospital cost (Table 4). The model was adjusted for numerous clinical and demographic variables. Age, gender, race, autologous transplant, tumor grade, diabetes, and liver disease were not significant predictors of hospital cost in the final model. The need for dialysis was associated with a 21% increase in hospital cost. Each percent increase in serum creatinine was associated with a 0.16% increase in cost. An interaction was identified between mechanical ventilation and sepsis (25% increase in hospital cost).
| VARIABLE | β | SE | P |
|---|---|---|---|
| Increase in creatinine (per 1%) | 0.00156 | 0.000257 | <0.001 |
| Dialysis | 0.213 | 0.0994 | 0.032 |
| Diuretics | 0.0831 | 0.0180 | <0.001 |
| Mechanical ventilation | 0.561 | 0.0299 | <0.001 |
| Allotransplant | 0.538 | 0.0960 | <0.001 |
| Medical vs. surgical service | 0.259 | 0.0381 | <0.001 |
| Liquid vs. solid tumor | 0.227 | 0.0433 | <0.001 |
| Distant vs. locoregional stage | 0.0717 | 0.0314 | 0.023 |
| Sepsis | 0.151 | 0.0622 | 0.015 |
| ER admission | −0.246 | 0.038 | <0.001 |
| Heart failure | 0.107 | 0.0469 | 0.023 |
| Hypertension | 0.0647 | 0.0271 | 0.017 |
| Mechanical ventilation × sepsis | 0.251 | 0.0853 | 0.003 |
| Constant | 10.8 | 0.0254 | <0.001 |
R2 = 0.32.
Discussion
The incidence of AKI in our study was 12.6% of all patients admitted to the ICU, and there was a progressive decrease in survival associated with worsening kidney injury. This association remained even after adjusting for covariates. AKI and the need for dialysis were also associated with increased hospital costs. To our knowledge, this is the largest single-center study to examine the RIFLE criteria for AKI in a critically-ill population with cancer.
A striking finding in our study is the significant effect that small elevations in serum creatinine may have on survival. An increase of 0.6 mg/dL in the RIFLE risk category increased the odds for mortality by a factor of 2.3 compared to patients without AKI. The median maximum creatinine in this group was only 1.3 mg/dL, which is still within the “normal” range for males in our institution. Criteria that define mild renal toxicity as a serum greater than “1.5 × the upper limit of normal” would exclude a significant number of patients in the RIFLE risk and injury categories, although their risk of mortality was significantly increased.[22] Other criteria that define AKI by glomerular filtration rate (GFR) are also problematic as estimating equations for GFR require serum creatinine to be in steady state. This is a false assumption to make in the setting of AKI, where serum creatinine may fluctuate daily. Serum creatinine is an insensitive marker of renal injury in patients with cancer, and more sensitive and specific biomarkers of AKI are currently under development.[23], [24] and [25] Until these markers are routinely available, renal injury in oncology practice and clinical trials may be better defined as a percentage rise in serum creatinine relative to baseline, similar to the RIFLE criteria.
Out of all variables examined, it is interesting that the need for dialysis had the greatest association with 60-day mortality (Table 3). Although we adjusted for other risk factors, there may still be residual confounding to explain the strong association of dialysis with mortality. However, it is also recognized that dialysis may promote a proinflammatory state[26] and that AKI, in itself, may lead to injury of distant organs via systemic cytokine release.[27] and [28] These deleterious effects may be amplified in patients with cancer, who frequently are neutropenic and have chronic inflammation (e.g. capillary leak syndrome, diffuse alveolar hemorrhage, graft-vs.-host disease). It is known that the need for dialysis after a stem cell transplant is associated with >70% mortality.[29] Although dialysis remains pivotal for volume and metabolic clearance, a true “therapy” for AKI has unfortunately remained elusive thus far.
Our overall incidence of 12.6% for AKI is lower than the reported incidence of 13%–42% in other studies of critically ill patients with cancer.[2], [30] and [31] We excluded patients who had a serum creatinine >1.5 mg/dL on admission to the ICU as we were interested in the development of AKI after ICU admission. This likely excluded patients who already had AKI on presentation, which may have contributed to the lower incidence of AKI and the need for dialysis in our study. Unlike previous studies, our cohort included a large number of patients on a surgical service who were electively admitted to the ICU for routine postoperative care and, therefore, were at lower risk of developing AKI. However, when limited to patients on a medical service, our incidence of 21% is consistent with the results of previous studies of patients in medical ICUs.
The prognosis of patients requiring dialysis was dismal, with an estimated 89% 60-day mortality. This is somewhat higher than the reported mortality of 66%–88% in previous studies.[32], [33], [34], [35] and [36] Given that our institution also serves as a referral cancer center for patients who have had progressive disease on standard therapy, it is possible that our patient population may have been more predisposed to complications from cancer therapy. Patients with hematological malignancies had a higher incidence of AKI and need for dialysis. However, underlying hematological malignancy and HCT were no longer significantly associated with 60-day mortality in the adjusted analysis. Similar to the findings of others, this would suggest that it is not the underlying malignancy itself but rather the complications of treatment and prolonged immunosuppression that lead to decreased survival in these patients.[37] and [38] Early goal-directed intensive life support should be considered for most patients,[39] but continuation of dialysis may not be of benefit, in terms of both survival and cost, in patients with hematologic malignancy who demonstrate minimal improvement.
Our study had certain limitations. Given the retrospective design, we cannot rule out selection bias or residual confounding. We were able to adjust for several variables specific to cancer and critical care as well as pre-ICU length of stay, which may be a surrogate marker for comorbidities and functional status. Nonetheless, our conclusions should be interpreted as hypothesis-generating. Second, our study is based on a single-center experience, which may limit its generalizability. Nonetheless, our study had a large sample size that was subjected to fairly uniform management. Third, we did not have data on end-of-life decisions, which may have impacted mortality and need for dialysis. Lastly, we were unable to obtain cost-to-charge ratios, which may limit the generalizability of our findings to other institutions. However, we reported on percent increases in cost as opposed to absolute dollar figures, which may adjust for some of this variation.
Conclusions
AKI as defined by the RIFLE criteria may be predictive of short-term mortality in critically ill patients with cancer. We have demonstrated that relatively small changes in serum creatinine are associated with higher mortality and that the need for dialysis entails a very poor prognosis. The mechanism behind the increased mortality in patients with hematological malignancies appears to be secondary to the associated complications of therapy, as opposed to the underlying cancer itself. We hypothesize that strategies to prevent the development of AKI and progression to dialysis dependence may improve survival. Whether the prevention of AKI translates to cost savings is also of interest.
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Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Volume 9, Issue 4, July-August 2011, Pages 149-155
Original research
Amit Lahoti MDa,
Background
Acute kidney injury (AKI) is a common complication in critically ill patients with cancer. The RIFLE criteria define three levels of AKI based on the percent increase in serum creatinine (Scr) from baseline: risk (≥50%), injury (≥100%), and failure (≥200% or requiring dialysis). The utility of the RIFLE criteria in critically ill patients with cancer is not known.
Objective
To examine the incidence, outcomes, and costs associated with AKI in critically ill patients with cancer.
Methods
We retrospectively analyzed all patients admitted to a single-center ICU over a 13-month period with a baseline Scr ≤1.5 mg/dL (n = 2,398). Kaplan-Meier estimates for survival by RIFLE category were calculated. Logistic regression was used to determine the association of AKI on 60-day mortality. A log-linear regression model was used for economic analysis. Costs were assessed by hospital charges from the provider's perspective.
Results
For the risk, injury, and failure categories of AKI, incidence rates were 6%, 2.8%, and 3.7%; 60-day survival estimates were 62%, 45%, and 14%; and adjusted odds ratios for 60-day mortality were 2.3, 3, and 14.3, respectively (P ≤ 0.001 compared to patients without AKI). Hematologic malignancy and hematopoietic cell transplant were not associated with mortality in the adjusted analysis. Hospital cost increased by 0.16% per 1% increase in creatinine and by 21% for patients requiring dialysis.
Limitations
Retrospective analysis. Single-center study. No adjustment by cost-to-charge ratios.
Conclusions
AKI is associated with higher mortality and costs in critically ill patients with cancer.
Over the past several years, important advances have occurred in the treatment and supportive care of critically ill patients with cancer.[1] However, acute kidney injury (AKI) remains a familiar complication and is a negative prognostic factor for overall survival.[2] and [3] The development of AKI can limit further cancer treatment, increase toxicity of chemotherapy and reduce its delivery, and exclude patients from clinical trials. Further, patients with AKI have been shown to have longer hospitalizations and increased hospital costs.[4] and [5] Recognized causes of AKI include acute tubular necrosis from medications or sepsis, volume depletion, tumor lysis syndrome, abdominal compartment syndrome, and obstruction from tumor or lymphadenopathy. Elevations in serum creatinine of as little as 0.3 mg/dL, which were previously considered insignificant, have been associated with a higher mortality rate in hospitalized patients.[4] However, few of the numerous definitions of AKI used in the cancer literature incorporate these subtle declines in kidney function.
An increase in serum creatinine has traditionally been used as a reflection of AKI. However, it is well known that elevation in serum creatinine is a relatively late marker of kidney injury.[6] In addition, patients with cancer often have decreased creatinine production secondary to cachexia, which may limit the sensitivity of creatinine as a marker of kidney injury. Other variables including total body volume, ethnicity, medications, and protein intake may also vary the serum creatinine level independent of renal function. Recent studies have demonstrated that a significant number of patients with cancer and normal serum creatinine have underlying chronic kidney disease (CKD) when renal function is estimated by the Cockcroft-Gault equation.[7] and [8] Therefore, using an arbitrarily defined level of serum creatinine as an indicator of AKI (i.e. >1.5 or 2.0 mg/dL) may not be suitable.
What may be a more accurate measure of kidney injury is a classification system based on the percent increase in serum creatinine relative to baseline. One such model is the Risk, Injury, Failure, Loss, and End-Stage Kidney (RIFLE) classification, which defines three levels of severity of AKI (risk, injury, and failure).[9] Previously, over 35 different definitions of AKI were used in the literature, which has made cross-comparisons between studies difficult.[10] The RIFLE classification provides a uniform definition of AKI and has been validated in numerous studies.[11], [12], [13], [14], [15], [16], [17] and [18] The aim of this analysis was to estimate the incidence, outcomes, and costs associated with AKI as defined by the RIFLE classification in critically ill patients with cancer.
Materials and Methods
The study included all patients ≥18 years of age who were admitted to the intensive care unit (ICU) at the University of Texas M.D. Anderson Cancer Center from December 2005 through December 2006. Patients with a baseline serum creatinine >1.5 mg/dL were excluded from the analysis. The protocol was approved by the institutional review board. Demographic and clinical data were obtained from the Department of Critical Care database, the Department of Pharmacy database, and the global institutional database (Enterprise Information Warehouse). The data were incorporated into a single spreadsheet using Excel 12.2 for Mac (Microsoft, Redmond, WA).
RIFLE categories for AKI were defined by the percent increase in serum creatinine from the time of ICU admission to the maximum creatinine at any point during the ICU stay: risk (≥50% rise in serum creatinine), injury (≥100% rise in serum creatinine), and failure (≥200% rise in serum creatinine). Consistent with the Acute Kidney Injury Network modifications of the original criteria, patients who required dialysis were classified into the RIFLE failure category, irrespective of the percent rise in serum creatinine.[19] The modality for continuous renal replacement therapy used at our institution is continuous slow low-efficiency dialysis (c-SLED), which has been described previously.[20] For patients who did not have an initial creatinine available within 24 hours after ICU admission, the most recent prior creatinine within the previous 48 hours was used.
Statistics
Descriptive data are presented as medians with interquartile ranges for continuous variables and absolute numbers with percentages for categorical variables. Survival of patients with AKI as defined by the RIFLE criteria was estimated by the Kaplan-Meier method. Patients were censored at death or last known follow-up, as determined by the clinical record. Statistical significance was determined by the log-rank test.
The primary end point for logistic regression was death at 60 days after ICU admission. Two separate models were developed, examining AKI as a categorical variable (RIFLE categories) and as a continuous variable (percent increase in creatinine from baseline). The variable “age” was significantly associated in a linear fashion with log odds of death but was dichotomized to provide a more meaningful odds ratio for the reader. Correlated data were assessed by correlation coefficients, and no variables were significantly correlated >0.6. Model reduction was achieved by variable elimination using the likelihood ratio test between nested models. Predictive ability and goodness-of-fit statistics were calculated, and the model was internally validated. No significant interactions were identified in either logistic regression model.
Lastly, a multivariate log linear regression model was developed to assess the relationship of AKI and dialysis with hospital cost. Cost was defined as hospital charges from the provider perspective. Log transformation of “cost” was used to account for skewness and heteroskedasticity. Coefficients in this model were multiplied by a factor of 100 to estimate a percent change in the dependent variable (cost) associated with a unit change in the independent variable.[21]
A two-tailed P < 0.05 was considered statistically significant. No patients were excluded from the analysis because of missing data. Statistical analysis was performed with Stata 10 for Mac (StataCorp, College Station, TX).
Results
The data set included 2,398 patients. Patient characteristics are listed in Table 1. The median age was 59 years. The cohort was predominantly Caucasian (75%) and relatively balanced with respect to gender. The majority of patients on a medical service were admitted to the hospital from the emergency room (76%), compared to only 10% of patients on a surgical service. Sepsis was diagnosed in 23% of patients on a medical service vs. only 4% of patients on a surgical service. This is consistent with the large number of patients at our institution who were admitted to the ICU for routine monitoring after elective surgeries. A significant number of patients had underlying hypertension and diabetes (54% and 18%, respectively). One-third of patients had advanced malignancy by Surveillance, Epidemiology, and End Results (SEER) stage on initial presentation to our institution.
b Included if patient received therapy at any time from ICU admission to date of maximum creatinine.
The absolute number of patients developing AKI or requiring dialysis by hospital service is depicted in Figure 1. The incidence of AKI was higher among patients on a medical vs. a surgical service (21% vs. 6.6%). Patients with hematologic malignancies (leukemia, lymphoma, and myeloma) had the highest incidence of AKI and need for dialysis (28% and 9.3%, respectively). Among patients on a medical service, the odds for developing AKI or requiring dialysis were increased 1.9-fold and 5.4-fold, respectively, for patients with an underlying hematologic malignancy.
Figure 1.
Number of Patients with AKI or Needing Dialysis by Hospital Service
AKI, defined as a minimum 50% increase in serum creatinine from baseline, occurred in 301 patients (12.6%), of whom 56 (2.3%) required dialysis. By further defining AKI by the RIFLE criteria, we classified 6%, 3%, and 4% of patients into the RIFLE risk, injury, and failure categories, respectively. The median elevations in creatinine from baseline were 0.6, 1.1, and 2 mg/dL, respectively. The median time to maximum creatinine was two days for all patients with AKI. There was a stepwise decrease in estimated survival associated with each RIFLE category (Figure 2). Among patients in the RIFLE failure group, the estimated survival was similar between those who required dialysis and those who did not (P = 0.99, log-rank). Although survival for patients requiring dialysis was dismal overall, it was significantly worse for patients with underlying hematological malignancy vs. solid tumor (3% vs. 20%, respectively).
The results of the logistic regression model for predictors of death at 60 days after ICU admission is presented in Table 2. Race and gender were not significant on univariate or multivariate analyses. Although significant on univariate analysis, hematologic malignancy, prior hematopoietic cell transplant (HCT), baseline comorbidities (hypertension, diabetes, heart failure, liver disease), and sepsis were also eliminated during model reduction. After adjusting for the remaining covariates, the RIFLE risk, injury, and failure categories remained significantly associated with 60-day mortality with odds ratios of 2.3, 3.0, and 14, respectively.
| VARIABLE | UNIVARIATE | MULTIVARIATE | |||
|---|---|---|---|---|---|
| OR | P | OR | 95% CI | P | |
| Age ≥55 years | 1.2 | 0.08 | 1.5 | 1.1–1.9 | 0.007 |
| Male vs. female | 0.997 | 0.98 | |||
| Ethnicity | |||||
| Black vs. white | 2.0 | <0.001 | |||
| Hispanic vs. white | 1.1 | 0.39 | |||
| Other vs. white | 0.8 | 0.46 | |||
| Hypertension | 1.3 | 0.02 | |||
| Diabetes | 1.6 | <0.001 | |||
| Heart failure | 2.5 | <0.001 | |||
| Chronic liver disease | 1.8 | 0.02 | |||
| RIFLE category | |||||
| Risk vs. no AKI | 4.1 | <0.001 | 2.3 | 1.5–3.6 | <0.001 |
| Injury vs. no AKI | 8.1 | <0.001 | 3.0 | 1.6–5.8 | 0.001 |
| Failure vs. no AKI | 35 | <0.001 | 14.3 | 7.2–29.0 | <0.001 |
| Amphotericin | 10.9 | <0.001 | 1.9 | 1.1–3.3 | 0.03 |
| Vasopressors | 6.3 | <0.001 | 2.0 | 1.4–2.6 | <0.001 |
| Mechanical ventilation | 2.1 | <0.001 | 1.9 | 1.4–2.5 | <0.001 |
| IV diuretics | 3.8 | <0.001 | 1.4 | 1.1–1.9 | 0.015 |
| Sepsis | 5.7 | <0.001 | |||
| Medical vs. surgical service | 9.9 | <0.001 | 2.2 | 1.5–3.1 | <0.001 |
| Liquid vs. solid tumor | 5.5 | <0.001 | |||
| Prior HCT | |||||
| Autologous | 1.7 | 0.23 | |||
| Allogeneic | 6.0 | <0.001 | |||
| Advanced vs. locoregional stage (SEER) | 4.4 | <0.001 | 2.1 | 1.6–2.6 | <0.001 |
| ER admission | 11.3 | <0.001 | 5.3 | 3.7–7.6 | <0.001 |
| Pre-ICU length of stay | 1.06 | <0.001 | 1.02 | 1.0–1.03 | 0.02 |
Likelihood ratio x2(12) = 818 (P < 0.001), positive predictive value 72%, negative predictive value 88%; area under the receiver operating curve = 0.88, Hosmer-Lemeshow x2(8) = 6.8 (P = 0.56).
OR, odds ratio; AKI, acute kidney injury; HCT, hematopoietic cell transplant; ER, emergency room; ICU, intensive care unit.
To further assess the relationship between serum creatinine and mortality, a separate logistic regression was performed using “percent rise in creatinine” as a continuous predictor variable (Table 3). Need for dialysis was also included as an independent variable. Aside from “percent rise in creatinine” and dialysis, model reduction yielded the same covariates as in the initial model. Dialysis had the largest effect on the odds of 60-day mortality (odds ratio = 6.2). After adjusting for dialysis, “percent rise in creatinine” remained significantly associated with 60-day mortality. For example, a 10% rise in creatinine increased the odds of mortality by 8%. The predictive capabilities of both logistic regression models were similar.
| VARIABLE | OR | 95% CI | P |
|---|---|---|---|
| Age ≥55 years | 1.4 | 1.1–1.9 | <0.001 |
| Percent increase in creatinine | 1.008 | 1.005–1.01 | <0.001 |
| ER admission | 5.4 | 3.8–7.7 | <0.001 |
| Pre-ICU length of stay (days) | 1.02 | 1.00–1.04 | 0.016 |
| SEER stage (distant vs. other) | 2.0 | 1.6–2.7 | <0.001 |
| Medical vs. surgical service | 2.2 | 1.5–3.2 | <0.001 |
| Vasopressors | 2.0 | 1.5–2.7 | <0.001 |
| Mechanical ventilation | 1.8 | 1.4–2.5 | <0.001 |
| Amphotericin | 1.8 | 1.1–3.2 | 0.031 |
| IV diuretics | 1.4 | 1.0–1.8 | 0.024 |
| Dialysis | 6.2 | 2.3–16.5 | <0.001 |
Likelihood ratio x2(11) = 815 (P < 0.001), positive predictive value 72%, negative predictive value 88%, area under the receiver operating curve = 0.88.
OR, odds ratio; ICU, intensive care unit; AKI, acute kidney injury; ER, emergency room.
We included AKI as a continuous variable in a multivariate regression to determine the relationship of AKI and dialysis with hospital cost (Table 4). The model was adjusted for numerous clinical and demographic variables. Age, gender, race, autologous transplant, tumor grade, diabetes, and liver disease were not significant predictors of hospital cost in the final model. The need for dialysis was associated with a 21% increase in hospital cost. Each percent increase in serum creatinine was associated with a 0.16% increase in cost. An interaction was identified between mechanical ventilation and sepsis (25% increase in hospital cost).
| VARIABLE | β | SE | P |
|---|---|---|---|
| Increase in creatinine (per 1%) | 0.00156 | 0.000257 | <0.001 |
| Dialysis | 0.213 | 0.0994 | 0.032 |
| Diuretics | 0.0831 | 0.0180 | <0.001 |
| Mechanical ventilation | 0.561 | 0.0299 | <0.001 |
| Allotransplant | 0.538 | 0.0960 | <0.001 |
| Medical vs. surgical service | 0.259 | 0.0381 | <0.001 |
| Liquid vs. solid tumor | 0.227 | 0.0433 | <0.001 |
| Distant vs. locoregional stage | 0.0717 | 0.0314 | 0.023 |
| Sepsis | 0.151 | 0.0622 | 0.015 |
| ER admission | −0.246 | 0.038 | <0.001 |
| Heart failure | 0.107 | 0.0469 | 0.023 |
| Hypertension | 0.0647 | 0.0271 | 0.017 |
| Mechanical ventilation × sepsis | 0.251 | 0.0853 | 0.003 |
| Constant | 10.8 | 0.0254 | <0.001 |
R2 = 0.32.
Discussion
The incidence of AKI in our study was 12.6% of all patients admitted to the ICU, and there was a progressive decrease in survival associated with worsening kidney injury. This association remained even after adjusting for covariates. AKI and the need for dialysis were also associated with increased hospital costs. To our knowledge, this is the largest single-center study to examine the RIFLE criteria for AKI in a critically-ill population with cancer.
A striking finding in our study is the significant effect that small elevations in serum creatinine may have on survival. An increase of 0.6 mg/dL in the RIFLE risk category increased the odds for mortality by a factor of 2.3 compared to patients without AKI. The median maximum creatinine in this group was only 1.3 mg/dL, which is still within the “normal” range for males in our institution. Criteria that define mild renal toxicity as a serum greater than “1.5 × the upper limit of normal” would exclude a significant number of patients in the RIFLE risk and injury categories, although their risk of mortality was significantly increased.[22] Other criteria that define AKI by glomerular filtration rate (GFR) are also problematic as estimating equations for GFR require serum creatinine to be in steady state. This is a false assumption to make in the setting of AKI, where serum creatinine may fluctuate daily. Serum creatinine is an insensitive marker of renal injury in patients with cancer, and more sensitive and specific biomarkers of AKI are currently under development.[23], [24] and [25] Until these markers are routinely available, renal injury in oncology practice and clinical trials may be better defined as a percentage rise in serum creatinine relative to baseline, similar to the RIFLE criteria.
Out of all variables examined, it is interesting that the need for dialysis had the greatest association with 60-day mortality (Table 3). Although we adjusted for other risk factors, there may still be residual confounding to explain the strong association of dialysis with mortality. However, it is also recognized that dialysis may promote a proinflammatory state[26] and that AKI, in itself, may lead to injury of distant organs via systemic cytokine release.[27] and [28] These deleterious effects may be amplified in patients with cancer, who frequently are neutropenic and have chronic inflammation (e.g. capillary leak syndrome, diffuse alveolar hemorrhage, graft-vs.-host disease). It is known that the need for dialysis after a stem cell transplant is associated with >70% mortality.[29] Although dialysis remains pivotal for volume and metabolic clearance, a true “therapy” for AKI has unfortunately remained elusive thus far.
Our overall incidence of 12.6% for AKI is lower than the reported incidence of 13%–42% in other studies of critically ill patients with cancer.[2], [30] and [31] We excluded patients who had a serum creatinine >1.5 mg/dL on admission to the ICU as we were interested in the development of AKI after ICU admission. This likely excluded patients who already had AKI on presentation, which may have contributed to the lower incidence of AKI and the need for dialysis in our study. Unlike previous studies, our cohort included a large number of patients on a surgical service who were electively admitted to the ICU for routine postoperative care and, therefore, were at lower risk of developing AKI. However, when limited to patients on a medical service, our incidence of 21% is consistent with the results of previous studies of patients in medical ICUs.
The prognosis of patients requiring dialysis was dismal, with an estimated 89% 60-day mortality. This is somewhat higher than the reported mortality of 66%–88% in previous studies.[32], [33], [34], [35] and [36] Given that our institution also serves as a referral cancer center for patients who have had progressive disease on standard therapy, it is possible that our patient population may have been more predisposed to complications from cancer therapy. Patients with hematological malignancies had a higher incidence of AKI and need for dialysis. However, underlying hematological malignancy and HCT were no longer significantly associated with 60-day mortality in the adjusted analysis. Similar to the findings of others, this would suggest that it is not the underlying malignancy itself but rather the complications of treatment and prolonged immunosuppression that lead to decreased survival in these patients.[37] and [38] Early goal-directed intensive life support should be considered for most patients,[39] but continuation of dialysis may not be of benefit, in terms of both survival and cost, in patients with hematologic malignancy who demonstrate minimal improvement.
Our study had certain limitations. Given the retrospective design, we cannot rule out selection bias or residual confounding. We were able to adjust for several variables specific to cancer and critical care as well as pre-ICU length of stay, which may be a surrogate marker for comorbidities and functional status. Nonetheless, our conclusions should be interpreted as hypothesis-generating. Second, our study is based on a single-center experience, which may limit its generalizability. Nonetheless, our study had a large sample size that was subjected to fairly uniform management. Third, we did not have data on end-of-life decisions, which may have impacted mortality and need for dialysis. Lastly, we were unable to obtain cost-to-charge ratios, which may limit the generalizability of our findings to other institutions. However, we reported on percent increases in cost as opposed to absolute dollar figures, which may adjust for some of this variation.
Conclusions
AKI as defined by the RIFLE criteria may be predictive of short-term mortality in critically ill patients with cancer. We have demonstrated that relatively small changes in serum creatinine are associated with higher mortality and that the need for dialysis entails a very poor prognosis. The mechanism behind the increased mortality in patients with hematological malignancies appears to be secondary to the associated complications of therapy, as opposed to the underlying cancer itself. We hypothesize that strategies to prevent the development of AKI and progression to dialysis dependence may improve survival. Whether the prevention of AKI translates to cost savings is also of interest.
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Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Volume 9, Issue 4, July-August 2011, Pages 149-155
Original research
Amit Lahoti MDa,
Background
Acute kidney injury (AKI) is a common complication in critically ill patients with cancer. The RIFLE criteria define three levels of AKI based on the percent increase in serum creatinine (Scr) from baseline: risk (≥50%), injury (≥100%), and failure (≥200% or requiring dialysis). The utility of the RIFLE criteria in critically ill patients with cancer is not known.
Objective
To examine the incidence, outcomes, and costs associated with AKI in critically ill patients with cancer.
Methods
We retrospectively analyzed all patients admitted to a single-center ICU over a 13-month period with a baseline Scr ≤1.5 mg/dL (n = 2,398). Kaplan-Meier estimates for survival by RIFLE category were calculated. Logistic regression was used to determine the association of AKI on 60-day mortality. A log-linear regression model was used for economic analysis. Costs were assessed by hospital charges from the provider's perspective.
Results
For the risk, injury, and failure categories of AKI, incidence rates were 6%, 2.8%, and 3.7%; 60-day survival estimates were 62%, 45%, and 14%; and adjusted odds ratios for 60-day mortality were 2.3, 3, and 14.3, respectively (P ≤ 0.001 compared to patients without AKI). Hematologic malignancy and hematopoietic cell transplant were not associated with mortality in the adjusted analysis. Hospital cost increased by 0.16% per 1% increase in creatinine and by 21% for patients requiring dialysis.
Limitations
Retrospective analysis. Single-center study. No adjustment by cost-to-charge ratios.
Conclusions
AKI is associated with higher mortality and costs in critically ill patients with cancer.
Over the past several years, important advances have occurred in the treatment and supportive care of critically ill patients with cancer.[1] However, acute kidney injury (AKI) remains a familiar complication and is a negative prognostic factor for overall survival.[2] and [3] The development of AKI can limit further cancer treatment, increase toxicity of chemotherapy and reduce its delivery, and exclude patients from clinical trials. Further, patients with AKI have been shown to have longer hospitalizations and increased hospital costs.[4] and [5] Recognized causes of AKI include acute tubular necrosis from medications or sepsis, volume depletion, tumor lysis syndrome, abdominal compartment syndrome, and obstruction from tumor or lymphadenopathy. Elevations in serum creatinine of as little as 0.3 mg/dL, which were previously considered insignificant, have been associated with a higher mortality rate in hospitalized patients.[4] However, few of the numerous definitions of AKI used in the cancer literature incorporate these subtle declines in kidney function.
An increase in serum creatinine has traditionally been used as a reflection of AKI. However, it is well known that elevation in serum creatinine is a relatively late marker of kidney injury.[6] In addition, patients with cancer often have decreased creatinine production secondary to cachexia, which may limit the sensitivity of creatinine as a marker of kidney injury. Other variables including total body volume, ethnicity, medications, and protein intake may also vary the serum creatinine level independent of renal function. Recent studies have demonstrated that a significant number of patients with cancer and normal serum creatinine have underlying chronic kidney disease (CKD) when renal function is estimated by the Cockcroft-Gault equation.[7] and [8] Therefore, using an arbitrarily defined level of serum creatinine as an indicator of AKI (i.e. >1.5 or 2.0 mg/dL) may not be suitable.
What may be a more accurate measure of kidney injury is a classification system based on the percent increase in serum creatinine relative to baseline. One such model is the Risk, Injury, Failure, Loss, and End-Stage Kidney (RIFLE) classification, which defines three levels of severity of AKI (risk, injury, and failure).[9] Previously, over 35 different definitions of AKI were used in the literature, which has made cross-comparisons between studies difficult.[10] The RIFLE classification provides a uniform definition of AKI and has been validated in numerous studies.[11], [12], [13], [14], [15], [16], [17] and [18] The aim of this analysis was to estimate the incidence, outcomes, and costs associated with AKI as defined by the RIFLE classification in critically ill patients with cancer.
Materials and Methods
The study included all patients ≥18 years of age who were admitted to the intensive care unit (ICU) at the University of Texas M.D. Anderson Cancer Center from December 2005 through December 2006. Patients with a baseline serum creatinine >1.5 mg/dL were excluded from the analysis. The protocol was approved by the institutional review board. Demographic and clinical data were obtained from the Department of Critical Care database, the Department of Pharmacy database, and the global institutional database (Enterprise Information Warehouse). The data were incorporated into a single spreadsheet using Excel 12.2 for Mac (Microsoft, Redmond, WA).
RIFLE categories for AKI were defined by the percent increase in serum creatinine from the time of ICU admission to the maximum creatinine at any point during the ICU stay: risk (≥50% rise in serum creatinine), injury (≥100% rise in serum creatinine), and failure (≥200% rise in serum creatinine). Consistent with the Acute Kidney Injury Network modifications of the original criteria, patients who required dialysis were classified into the RIFLE failure category, irrespective of the percent rise in serum creatinine.[19] The modality for continuous renal replacement therapy used at our institution is continuous slow low-efficiency dialysis (c-SLED), which has been described previously.[20] For patients who did not have an initial creatinine available within 24 hours after ICU admission, the most recent prior creatinine within the previous 48 hours was used.
Statistics
Descriptive data are presented as medians with interquartile ranges for continuous variables and absolute numbers with percentages for categorical variables. Survival of patients with AKI as defined by the RIFLE criteria was estimated by the Kaplan-Meier method. Patients were censored at death or last known follow-up, as determined by the clinical record. Statistical significance was determined by the log-rank test.
The primary end point for logistic regression was death at 60 days after ICU admission. Two separate models were developed, examining AKI as a categorical variable (RIFLE categories) and as a continuous variable (percent increase in creatinine from baseline). The variable “age” was significantly associated in a linear fashion with log odds of death but was dichotomized to provide a more meaningful odds ratio for the reader. Correlated data were assessed by correlation coefficients, and no variables were significantly correlated >0.6. Model reduction was achieved by variable elimination using the likelihood ratio test between nested models. Predictive ability and goodness-of-fit statistics were calculated, and the model was internally validated. No significant interactions were identified in either logistic regression model.
Lastly, a multivariate log linear regression model was developed to assess the relationship of AKI and dialysis with hospital cost. Cost was defined as hospital charges from the provider perspective. Log transformation of “cost” was used to account for skewness and heteroskedasticity. Coefficients in this model were multiplied by a factor of 100 to estimate a percent change in the dependent variable (cost) associated with a unit change in the independent variable.[21]
A two-tailed P < 0.05 was considered statistically significant. No patients were excluded from the analysis because of missing data. Statistical analysis was performed with Stata 10 for Mac (StataCorp, College Station, TX).
Results
The data set included 2,398 patients. Patient characteristics are listed in Table 1. The median age was 59 years. The cohort was predominantly Caucasian (75%) and relatively balanced with respect to gender. The majority of patients on a medical service were admitted to the hospital from the emergency room (76%), compared to only 10% of patients on a surgical service. Sepsis was diagnosed in 23% of patients on a medical service vs. only 4% of patients on a surgical service. This is consistent with the large number of patients at our institution who were admitted to the ICU for routine monitoring after elective surgeries. A significant number of patients had underlying hypertension and diabetes (54% and 18%, respectively). One-third of patients had advanced malignancy by Surveillance, Epidemiology, and End Results (SEER) stage on initial presentation to our institution.
b Included if patient received therapy at any time from ICU admission to date of maximum creatinine.
The absolute number of patients developing AKI or requiring dialysis by hospital service is depicted in Figure 1. The incidence of AKI was higher among patients on a medical vs. a surgical service (21% vs. 6.6%). Patients with hematologic malignancies (leukemia, lymphoma, and myeloma) had the highest incidence of AKI and need for dialysis (28% and 9.3%, respectively). Among patients on a medical service, the odds for developing AKI or requiring dialysis were increased 1.9-fold and 5.4-fold, respectively, for patients with an underlying hematologic malignancy.
Figure 1.
Number of Patients with AKI or Needing Dialysis by Hospital Service
AKI, defined as a minimum 50% increase in serum creatinine from baseline, occurred in 301 patients (12.6%), of whom 56 (2.3%) required dialysis. By further defining AKI by the RIFLE criteria, we classified 6%, 3%, and 4% of patients into the RIFLE risk, injury, and failure categories, respectively. The median elevations in creatinine from baseline were 0.6, 1.1, and 2 mg/dL, respectively. The median time to maximum creatinine was two days for all patients with AKI. There was a stepwise decrease in estimated survival associated with each RIFLE category (Figure 2). Among patients in the RIFLE failure group, the estimated survival was similar between those who required dialysis and those who did not (P = 0.99, log-rank). Although survival for patients requiring dialysis was dismal overall, it was significantly worse for patients with underlying hematological malignancy vs. solid tumor (3% vs. 20%, respectively).
The results of the logistic regression model for predictors of death at 60 days after ICU admission is presented in Table 2. Race and gender were not significant on univariate or multivariate analyses. Although significant on univariate analysis, hematologic malignancy, prior hematopoietic cell transplant (HCT), baseline comorbidities (hypertension, diabetes, heart failure, liver disease), and sepsis were also eliminated during model reduction. After adjusting for the remaining covariates, the RIFLE risk, injury, and failure categories remained significantly associated with 60-day mortality with odds ratios of 2.3, 3.0, and 14, respectively.
| VARIABLE | UNIVARIATE | MULTIVARIATE | |||
|---|---|---|---|---|---|
| OR | P | OR | 95% CI | P | |
| Age ≥55 years | 1.2 | 0.08 | 1.5 | 1.1–1.9 | 0.007 |
| Male vs. female | 0.997 | 0.98 | |||
| Ethnicity | |||||
| Black vs. white | 2.0 | <0.001 | |||
| Hispanic vs. white | 1.1 | 0.39 | |||
| Other vs. white | 0.8 | 0.46 | |||
| Hypertension | 1.3 | 0.02 | |||
| Diabetes | 1.6 | <0.001 | |||
| Heart failure | 2.5 | <0.001 | |||
| Chronic liver disease | 1.8 | 0.02 | |||
| RIFLE category | |||||
| Risk vs. no AKI | 4.1 | <0.001 | 2.3 | 1.5–3.6 | <0.001 |
| Injury vs. no AKI | 8.1 | <0.001 | 3.0 | 1.6–5.8 | 0.001 |
| Failure vs. no AKI | 35 | <0.001 | 14.3 | 7.2–29.0 | <0.001 |
| Amphotericin | 10.9 | <0.001 | 1.9 | 1.1–3.3 | 0.03 |
| Vasopressors | 6.3 | <0.001 | 2.0 | 1.4–2.6 | <0.001 |
| Mechanical ventilation | 2.1 | <0.001 | 1.9 | 1.4–2.5 | <0.001 |
| IV diuretics | 3.8 | <0.001 | 1.4 | 1.1–1.9 | 0.015 |
| Sepsis | 5.7 | <0.001 | |||
| Medical vs. surgical service | 9.9 | <0.001 | 2.2 | 1.5–3.1 | <0.001 |
| Liquid vs. solid tumor | 5.5 | <0.001 | |||
| Prior HCT | |||||
| Autologous | 1.7 | 0.23 | |||
| Allogeneic | 6.0 | <0.001 | |||
| Advanced vs. locoregional stage (SEER) | 4.4 | <0.001 | 2.1 | 1.6–2.6 | <0.001 |
| ER admission | 11.3 | <0.001 | 5.3 | 3.7–7.6 | <0.001 |
| Pre-ICU length of stay | 1.06 | <0.001 | 1.02 | 1.0–1.03 | 0.02 |
Likelihood ratio x2(12) = 818 (P < 0.001), positive predictive value 72%, negative predictive value 88%; area under the receiver operating curve = 0.88, Hosmer-Lemeshow x2(8) = 6.8 (P = 0.56).
OR, odds ratio; AKI, acute kidney injury; HCT, hematopoietic cell transplant; ER, emergency room; ICU, intensive care unit.
To further assess the relationship between serum creatinine and mortality, a separate logistic regression was performed using “percent rise in creatinine” as a continuous predictor variable (Table 3). Need for dialysis was also included as an independent variable. Aside from “percent rise in creatinine” and dialysis, model reduction yielded the same covariates as in the initial model. Dialysis had the largest effect on the odds of 60-day mortality (odds ratio = 6.2). After adjusting for dialysis, “percent rise in creatinine” remained significantly associated with 60-day mortality. For example, a 10% rise in creatinine increased the odds of mortality by 8%. The predictive capabilities of both logistic regression models were similar.
| VARIABLE | OR | 95% CI | P |
|---|---|---|---|
| Age ≥55 years | 1.4 | 1.1–1.9 | <0.001 |
| Percent increase in creatinine | 1.008 | 1.005–1.01 | <0.001 |
| ER admission | 5.4 | 3.8–7.7 | <0.001 |
| Pre-ICU length of stay (days) | 1.02 | 1.00–1.04 | 0.016 |
| SEER stage (distant vs. other) | 2.0 | 1.6–2.7 | <0.001 |
| Medical vs. surgical service | 2.2 | 1.5–3.2 | <0.001 |
| Vasopressors | 2.0 | 1.5–2.7 | <0.001 |
| Mechanical ventilation | 1.8 | 1.4–2.5 | <0.001 |
| Amphotericin | 1.8 | 1.1–3.2 | 0.031 |
| IV diuretics | 1.4 | 1.0–1.8 | 0.024 |
| Dialysis | 6.2 | 2.3–16.5 | <0.001 |
Likelihood ratio x2(11) = 815 (P < 0.001), positive predictive value 72%, negative predictive value 88%, area under the receiver operating curve = 0.88.
OR, odds ratio; ICU, intensive care unit; AKI, acute kidney injury; ER, emergency room.
We included AKI as a continuous variable in a multivariate regression to determine the relationship of AKI and dialysis with hospital cost (Table 4). The model was adjusted for numerous clinical and demographic variables. Age, gender, race, autologous transplant, tumor grade, diabetes, and liver disease were not significant predictors of hospital cost in the final model. The need for dialysis was associated with a 21% increase in hospital cost. Each percent increase in serum creatinine was associated with a 0.16% increase in cost. An interaction was identified between mechanical ventilation and sepsis (25% increase in hospital cost).
| VARIABLE | β | SE | P |
|---|---|---|---|
| Increase in creatinine (per 1%) | 0.00156 | 0.000257 | <0.001 |
| Dialysis | 0.213 | 0.0994 | 0.032 |
| Diuretics | 0.0831 | 0.0180 | <0.001 |
| Mechanical ventilation | 0.561 | 0.0299 | <0.001 |
| Allotransplant | 0.538 | 0.0960 | <0.001 |
| Medical vs. surgical service | 0.259 | 0.0381 | <0.001 |
| Liquid vs. solid tumor | 0.227 | 0.0433 | <0.001 |
| Distant vs. locoregional stage | 0.0717 | 0.0314 | 0.023 |
| Sepsis | 0.151 | 0.0622 | 0.015 |
| ER admission | −0.246 | 0.038 | <0.001 |
| Heart failure | 0.107 | 0.0469 | 0.023 |
| Hypertension | 0.0647 | 0.0271 | 0.017 |
| Mechanical ventilation × sepsis | 0.251 | 0.0853 | 0.003 |
| Constant | 10.8 | 0.0254 | <0.001 |
R2 = 0.32.
Discussion
The incidence of AKI in our study was 12.6% of all patients admitted to the ICU, and there was a progressive decrease in survival associated with worsening kidney injury. This association remained even after adjusting for covariates. AKI and the need for dialysis were also associated with increased hospital costs. To our knowledge, this is the largest single-center study to examine the RIFLE criteria for AKI in a critically-ill population with cancer.
A striking finding in our study is the significant effect that small elevations in serum creatinine may have on survival. An increase of 0.6 mg/dL in the RIFLE risk category increased the odds for mortality by a factor of 2.3 compared to patients without AKI. The median maximum creatinine in this group was only 1.3 mg/dL, which is still within the “normal” range for males in our institution. Criteria that define mild renal toxicity as a serum greater than “1.5 × the upper limit of normal” would exclude a significant number of patients in the RIFLE risk and injury categories, although their risk of mortality was significantly increased.[22] Other criteria that define AKI by glomerular filtration rate (GFR) are also problematic as estimating equations for GFR require serum creatinine to be in steady state. This is a false assumption to make in the setting of AKI, where serum creatinine may fluctuate daily. Serum creatinine is an insensitive marker of renal injury in patients with cancer, and more sensitive and specific biomarkers of AKI are currently under development.[23], [24] and [25] Until these markers are routinely available, renal injury in oncology practice and clinical trials may be better defined as a percentage rise in serum creatinine relative to baseline, similar to the RIFLE criteria.
Out of all variables examined, it is interesting that the need for dialysis had the greatest association with 60-day mortality (Table 3). Although we adjusted for other risk factors, there may still be residual confounding to explain the strong association of dialysis with mortality. However, it is also recognized that dialysis may promote a proinflammatory state[26] and that AKI, in itself, may lead to injury of distant organs via systemic cytokine release.[27] and [28] These deleterious effects may be amplified in patients with cancer, who frequently are neutropenic and have chronic inflammation (e.g. capillary leak syndrome, diffuse alveolar hemorrhage, graft-vs.-host disease). It is known that the need for dialysis after a stem cell transplant is associated with >70% mortality.[29] Although dialysis remains pivotal for volume and metabolic clearance, a true “therapy” for AKI has unfortunately remained elusive thus far.
Our overall incidence of 12.6% for AKI is lower than the reported incidence of 13%–42% in other studies of critically ill patients with cancer.[2], [30] and [31] We excluded patients who had a serum creatinine >1.5 mg/dL on admission to the ICU as we were interested in the development of AKI after ICU admission. This likely excluded patients who already had AKI on presentation, which may have contributed to the lower incidence of AKI and the need for dialysis in our study. Unlike previous studies, our cohort included a large number of patients on a surgical service who were electively admitted to the ICU for routine postoperative care and, therefore, were at lower risk of developing AKI. However, when limited to patients on a medical service, our incidence of 21% is consistent with the results of previous studies of patients in medical ICUs.
The prognosis of patients requiring dialysis was dismal, with an estimated 89% 60-day mortality. This is somewhat higher than the reported mortality of 66%–88% in previous studies.[32], [33], [34], [35] and [36] Given that our institution also serves as a referral cancer center for patients who have had progressive disease on standard therapy, it is possible that our patient population may have been more predisposed to complications from cancer therapy. Patients with hematological malignancies had a higher incidence of AKI and need for dialysis. However, underlying hematological malignancy and HCT were no longer significantly associated with 60-day mortality in the adjusted analysis. Similar to the findings of others, this would suggest that it is not the underlying malignancy itself but rather the complications of treatment and prolonged immunosuppression that lead to decreased survival in these patients.[37] and [38] Early goal-directed intensive life support should be considered for most patients,[39] but continuation of dialysis may not be of benefit, in terms of both survival and cost, in patients with hematologic malignancy who demonstrate minimal improvement.
Our study had certain limitations. Given the retrospective design, we cannot rule out selection bias or residual confounding. We were able to adjust for several variables specific to cancer and critical care as well as pre-ICU length of stay, which may be a surrogate marker for comorbidities and functional status. Nonetheless, our conclusions should be interpreted as hypothesis-generating. Second, our study is based on a single-center experience, which may limit its generalizability. Nonetheless, our study had a large sample size that was subjected to fairly uniform management. Third, we did not have data on end-of-life decisions, which may have impacted mortality and need for dialysis. Lastly, we were unable to obtain cost-to-charge ratios, which may limit the generalizability of our findings to other institutions. However, we reported on percent increases in cost as opposed to absolute dollar figures, which may adjust for some of this variation.
Conclusions
AKI as defined by the RIFLE criteria may be predictive of short-term mortality in critically ill patients with cancer. We have demonstrated that relatively small changes in serum creatinine are associated with higher mortality and that the need for dialysis entails a very poor prognosis. The mechanism behind the increased mortality in patients with hematological malignancies appears to be secondary to the associated complications of therapy, as opposed to the underlying cancer itself. We hypothesize that strategies to prevent the development of AKI and progression to dialysis dependence may improve survival. Whether the prevention of AKI translates to cost savings is also of interest.
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Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.