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Outcome for Cancer Patients Requiring Mechanical Ventilation

From the Memorial Sloan-Kettering Cancer Center, New York, NY; Johns Hopkins Hospital, Baltimore, MD; Mount Sinai Medical Center, New York, NY; City of Hope National Medical Center, Duarte, CA; and University of Texas M.D. Anderson Cancer Center, Houston, TX.

Address reprint requests to Jeffrey S. Groeger, MD, Critical Care Medicine Service, Memorial Hospital, 1275 York Ave, New York, NY 10021; email groegerj{at}mskcc.org

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
PURPOSE: To describe hospital survival for cancer patients who require mechanical ventilation.

MATERIALS AND METHODS: A prospective, multicenter observational study was performed at five academic tertiary care hospitals. Demographic and clinical variables were obtained on consecutive cancer patients at initiation of mechanical ventilation, and information on vital status at hospital discharge was acquired.

RESULTS: Our analysis was based on 782 adult cancer patients who met predetermined inclusion criteria. The overall observed hospital mortality was 76%, with no statistically significant differences among the five study centers. Seven variables (intubation after 24 hours, leukemia, progression or recurrence of cancer, allogeneic bone marrow transplantation, cardiac arrhythmias, presence of disseminated intravascular coagulation, and need for vasopressor therapy) were associated with an increased risk of death, whereas prior surgery with curative intent was protective. The predictive model based on these variables had an area under the receiver operating characteristic curve of 0.736, with Hosmer-Lemeshow goodness-of-fit statistics of 7.19; P = .52.

CONCLUSION: This model can be used to estimate the probability of hospital survival for classes of adult cancer patients who require mechanical ventilation and can help to guide physicians, patients, and families in deciding goals and direction of treatment. Prospective independent validation in different medical settings is warranted.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
APPROXIMATELY 20% of cancer patients die of respiratory failure (excluding pneumonia and pulmonary emboli).¹ Patients with cancer who require mechanical ventilation for respiratory failure have a grim prognosis.^1-16 Respiratory failure in cancer patients is typically a manifestation of advanced lung disease that does not, in general, respond to supportive care. The decision to mechanically ventilate a cancer patient with respiratory failure is often contentious. The cost in terms of dollars, emotional suffering, and failed expectations is extraordinarily high.

Currently, there are no models for predicting hospital survival in adult cancer patients who require mechanical ventilation for respiratory failure. We present the results of a multicenter study that describes clinical parameters predictive of hospital mortality for mechanically ventilated adult cancer patients.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Data were prospectively collected in five academic tertiary care hospitals beginning July 1, 1994, and ending August 30, 1996, to develop a multivariable logistic regression model to estimate the probability of hospital mortality among cancer patients requiring mechanical ventilation. Participating facilities were Memorial Sloan-Kettering Cancer Center (MSKCC), New York, NY; City of Hope National Medical Center, Duarte, CA; The University of Texas M.D. Anderson Cancer Center, Houston, TX; Mount Sinai Medical Center, New York, NY; and Johns Hopkins Hospital, Baltimore, MD. The study was approved by the institutional review boards of all participating sites.

All cancer patients requiring mechanical ventilation were included, with the exception of patients less than 16 years old, burn patients, coronary patients, who were defined by a primary diagnosis of myocardial infarction or "rule out myocardial infarction" with no secondary diagnosis, patients having surgery before intubation on current admission, as well as patients intubated for cardiopulmonary resuscitation who did not survive the acute resuscitation. The outcome of interest was vital status at hospital discharge. Patients discharged to another hospital for an increased (or same) level of care and patients transferred from another facility while intubated were not included in the analysis. For patients with multiple episodes of mechanical ventilation during the study period, only the first episode of the most recent admission was used in the analysis.

Demographic and clinical variables were obtained at intensive care unit (ICU) admission and within 1 hour of initiation of mechanical ventilation; in addition, the patient's vital status at hospital discharge was acquired. Patients were classified as being in one of four tumor groups: solid tumor, solid tumor with metastasis, leukemia, or lymphoma/myeloma (Table 1). Transplantation status was recorded as none, allogeneic, or autologous. Patients with leukemia, bone marrow transplant, lymphoma, or myeloma were classified as having nonmetastatic disease.

Variables were recorded in duplicate on standardized study forms and then entered into a computerized database available at each study center. A copy of the data form as well as the computer data were submitted to MSKCC for determination of quality and completeness of data entry. Validity checks for entry variables were incorporated within the study software. All computer entries were validated at MSKCC against the original paper copies before statistical analysis.

The response variable used in the analyses was hospital discharge vital status (alive or dead). Univariable analyses were performed using ² tests and t tests to examine the association between vital status and 34 potential prognostic factors representing demographic, disease, treatment, and comorbid characteristics of the patients. For most variables, values recorded just before ventilation were used in the analysis, except for performance status, for which the patient's status 1 week before hospitalization was used. A new continuous variable representing the time from hospitalization to ventilation (TTV) was created from the information collected for each patient on the date of hospitalization, date of admission to the ICU (equal to the date of ventilation for patients at Johns Hopkins, where patients were ventilated on the general oncology unit), and the categorical variable time from ICU admission to ventilation (recorded as "at admission," "within 24 hours," "within 72 hours," or "late"—with accompanying late ventilation date).

Univariable and multivariable exploratory analyses were performed on the continuous variable TTV to check whether logistic regression model assumptions were approximated or whether the variable had an underlying categorical form. First, for each quartile of the TTV variable, the proportion of patients who died was plotted against the midpoint of the quartile TTV values. The pattern was examined for any apparent trend in risk or for a steplike jump in the proportions at some value (suggesting a possible cut point for dichotomization). To repeat this process in a multivariable setting (ie, controlling for other prognostic factors), odds ratios based on a multivariable logistic regression model were generated for each quartile. The model used to generate the odds ratios contained all variables whose univariable tests resulted in a P < .10 and indicator variables representing the second, third, and fourth quartiles of the TTV variables. The coefficients of these indicator variables were then used to compute the odds of dying for patients in the ith (i = 2,3,4) quartile relative to the odds of dying for patients in the first TTV quartile. (Thus, the odds ratio for the first quartile was 1.0). These quartile odds ratios also were plotted against the midpoints of the quartile TTV values in a search for trends.¹⁷ These exploratory analyses were repeated on the other continuous variable, age.

After the TTV variable was dichotomized (age did not appear to be a candidate) and its individual significance was reassessed, all prognostic factors significantly associated with ICU outcome according to a univariable P < .10 criterion were entered into a multivariable logistic regression model. Stepwise and backward elimination regression procedures were used to further narrow down the subset of variables associated with ICU outcome. A Hosmer-Lemeshow goodness-of-fit statistic¹⁷ and area under the receiver operating characteristic (ROC) curve¹⁸ were computed as descriptive tools for examining the predictive value of the final set of variables. SAS release 6.12 (SAS Institute, Cary, NC) was used for all analyses.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Our analysis was based on 782 cancer patients who met all of the inclusion criteria. The number of patients from each site were MSKCC 229, M.D. Anderson 250, City of Hope 74, Mount Sinai 154, and Johns Hopkins 75. Overall hospital mortality was 76%, with no statistically significant difference in mortality among the five study centers. All patients at M.D. Anderson and City of Hope were cared for in an ICU setting. Fifteen patients at MSKCC and four patients at Mount Sinai were managed on the general medical wards. Decisions not to admit a patient to the ICU at MSKCC were based on ICU bed availability and at Mount Sinai on reluctance to transfer patients from the protective environment of the bone marrow transplantation (BMT) unit. At Johns Hopkins, three patients were initially admitted to the ICU but ultimately cared for on the general oncology unit, where point-of-care ICU management is the rule, ie, mechanically ventilated patients remain on the oncology unit, and monitoring equipment is available.

Categorization of patients by specific malignancy is presented in Table 1. Univariable analysis of continuous variables by t test reveals the age of survivors (mean ± SD) to be 58.0 ± 16.7 years versus 53.1 ± 15.8 years for decedents (P < .001). Mechanical ventilation was initiated 9.5 ± 16.6 days after hospitalization in survivors versus 12.7 ± 16.3 days in those who died (P = .018). Univariable analyses of categorical variables are presented in Table 2.

Disease status was categorized as no evidence of disease, newly diagnosed and currently under therapy, or disease progression or recurrence. The specific chemotherapeutic regimen was not recorded, although timing of intubation from the most recent chemotherapy was noted. Intent of prior surgery was recorded as none, curative, or palliative, and radiation history was classified as none, isolated port irradiation, or total-body irradiation.

Performance status 1 week before hospitalization was coded as normal (Eastern Cooperative Oncology Group [ECOG] 0,1), symptomatic (ECOG 2,3), or bedridden (ECOG 4). Indications for intubation were categorized into five groups: airway compromise, pulmonary hemorrhage/hemoptysis, hypoxic pulmonary failure, ventilatory failure, and other (usually, multiorgan system failure or circulatory/septic shock). Additionally, location of intubation was entered as emergency room or general hospital (ward, ICU, or BMT unit).

Table 3 presents results of multivariable logistic regression analysis. Eight variables were associated with increased risk of death after mechanical ventilation, whereas prior surgery with curative intent was protective. Disseminated intravascular coagulation (DIC) was defined as a combination of prolonged prothrombin time, prolonged partial thromboplastin time, hypofibrinogenemia, and thrombocytopenia in the proper clinical setting, or a peripheral smear consistent with DIC and positive supportive tests (prolonged prothrombin time, activated partial thromboplastin time, and thrombin time; decreased fibrinogen or platelets; positive fibrin/fibrinogen degradation products; or D-dimer). Cardiac dysrhythmia was coded as present for life-threatening arrhythmias: (1) ventricular tachycardia and fibrillation; (2) supraventricular dysrhythmia (paroxysmal atrial tachycardia, atrial fibrillation or flutter) associated with chest pain, shortness of breath, or decreased level of consciousness or signs of hypotension, shock, pulmonary edema, or congestion; or (3) new heart block (Mobitz type 2 second-degree or third-degree heart block). We did not include chronic or stable arrhythmias. Vasopressor therapy was coded as yes for an infusion of any dose of norepinephrine, epinephrine, phenylephrine, dobutamine, amrinone, milrinone, nitroprusside, nicardipine, or > 3 µg/kg/min dopamine lasting for at least 1 hour.

Using the original data, a Hosmer-Lemeshow goodness-of-fit statistic of 7.19 (P = .52) (Table 4) and an area under the ROC curve of 0.736 describe the calibration and discrimination of the final model. Model validation was not performed using subsets of the original 782 patients because of data sparsity for some variable combinations.

	DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
We present a descriptive model of clinical risk factors that can be used to estimate the probability of hospital mortality in adult cancer patients receiving mechanical ventilation for respiratory failure. The model is based on data collected from 782 patients collected at five tertiary hospitals. It is comprised of eight clinical variables that were defined by multivariable logistic regression and are readily obtainable at the time when mechanical ventilation is considered. The ROC area for this model is 0.736, comparable to mortality prediction models for general medical ICU patients.^19-21

The variables in the model segregate into two groups. Disease status or extent of underlying malignancy is represented by diagnostic tumor group, treatment status, transplantation status, and type of prior surgery (curative or palliative v none). Patients with leukemia or progressive malignancy who require mechanical ventilation are approximately twice as likely to die as patients without these factors. Patients who have undergone allogeneic BMT are approximately two times more likely to die than non-allogeneic BMT patients if they require mechanical ventilation. In contrast, patients who have undergone cancer surgery with curative intent during prior hospitalization and now require mechanical ventilation are approximately twice as likely not to die as patients who underwent palliative cancer surgery or had no cancer surgery at all.

Acute critical illness and/or major organ dysfunction are often accompanied by DIC, cardiac arrhythmias, and the need for vasopressors. Patients with cardiac arrhythmia(s) and those who require vasopressors are nearly two times more likely to die than cancer patients without these individual factors. Patients with DIC are roughly four times more likely to die than those without DIC. The negative impact of organ system failure on hospital survival in mechanically ventilated cancer patients was described by Snow et al¹; in their study, there were no 6-month survivors among mechanically ventilated cancer patients with four or more organ failures. Worse survival with increasing number of failing organ systems is well accepted in medical patients with adult respiratory distress syndrome complicated by multiorgan system failure.²²

Some variables in this model are found in other mortality prediction models for critically ill patients. Variables related to metastatic cancer, BMT, acute leukemia, lymphoma, cardiac arrhythmia, and hypotension are predictive of an increased likelihood of hospital mortality in general ICU mortality prediction models.^19-21 We have shown previously that disease relapse/progression as well as allogeneic BMT were predictive of hospital mortality in a large series of critically ill cancer patients.²³

The TTV (difference between admission and intubation dates) was a critical variable. Patients who developed respiratory failure requiring mechanical ventilation more than 1 day after admission were two times more likely to die than patients who were mechanically ventilated within 24 hours of admission. This likely reflects the effect of prior medical treatment. Patients presenting to the hospital with respiratory failure do better on average than patients who develop respiratory failure in the hospital, presumably having failed intensive in-hospital treatment. This segues to a related concept. Does the duration of mechanical ventilation predict death in cancer patients? The literature is divided on this issue. Six studies^11-16 (529 patients) reported 100% mortality in cancer patients who were mechanically ventilated for more than 10 days, whereas six other studies^1-6 (831 patients) found that the duration of mechanical ventilation was not an absolute predictor of death. It is unrealistic to expect that the number of days of mechanical ventilation will predict death with 100% sensitivity. However, it is important to acknowledge that cancer patients who require prolonged mechanical ventilation, like those who develop respiratory failure more than 24 hours after hospitalization, have an ominous prognosis.

This analysis has some weaknesses. It has not been validated in an independent group of cancer patients with respiratory failure. The model was derived from cancer patients treated in tertiary academic medical centers and may not apply to other types of hospitals. The decision to institute mechanical ventilation in cancer patients may show significant institutional variability, or the patients could be more likely to survive because they are less sick and/or receive superior care in other treatment settings. The data set was limited to the patients' first episode of respiratory failure during the study period, and therefore the model may not apply in other settings.

Furthermore, this model, like all prognostic scoring systems, should not be used in isolation to prognosticate on the likelihood for survival of an individual patient. This model may be used to enhance or augment clinical decision making by reducing uncertainty and improving reproducibility.²⁴ As noted above, the prognosis of cancer patients with respiratory failure requiring mechanical ventilation is uniformly grim (Table 5). Hospital mortality in this setting varies with the patients' underlying diagnosis and is approximately 95% for BMT patients,^{3-5,7,11,12,14} 75% to 90% for patients with hematologic malignancies,^{1,2,4,6,8-10,16} and 70% to 90% for patients with solid tumors.^1,10,13,15 These mortality figures are higher than the hospital mortality values reported for medical patients requiring mechanical ventilation for acute respiratory failure (31%),²⁵ adult respiratory distress syndrome (36%),²⁶ community-acquired pneumonia (36%),²⁷ or nosocomial ventilator-associated pneumonia (33%).²⁸ They are similar to the mortality figures reported in patients who require mechanical ventilation for AIDS-related Pneumocystis carinii pneumonia (81%),²⁹ bacteremic pneumococcal pneumonia (81%),³⁰ respiratory failure in patients more than 80 years of age who are mechanically ventilated for more than 15 days (91%),³¹ or critically ill patients with three or more failed organs for at least 3 days (98%).³²

The advisability of routinely offering mechanical ventilation to cancer patients with respiratory failure is suspect. The decision, often addressed after asking the patient or a surrogate if he or she wants everything possible to be done when the patient is in the throes of progressive respiratory insufficiency, should be individualized. Cancer patients and their families should be told the chance of long-term survival from mechanical ventilation before the recognition of incipient respiratory failure. Although it is important to offer mechanical ventilation and ICU care to patients with respiratory failure who have a reasonable chance of benefit, this can be a contentious issue. The debate has been most sharply focused with regard to BMT patients, for whom hospital survival in multiple series was uniformly bleak (~95% mortality). Crawford et al^11,33 held to the definition of medical futility as less than a 1% chance of survival, and they went to considerable lengths to define clinical scenarios in mechanically ventilated BMT patients for whom hospital survival was less than 1% (eg, patients with respiratory failure who either required vasopressors or had liver and renal failure).³³ This definition has been rejected by others, who believe that mechanical ventilation should not be routine care for BMT patients with respiratory failure.^5,12

Attempts to contain skyrocketing medical costs are certain to focus on the ICU, where ~5% of patients consume ~20% of the cost.¹⁵ In the future, it may become necessary to demonstrate that certain types of health care services are worth the cost. Subjective value judgments may be required, but treatment or care that is costly and is deemed to be of marginal benefit may not be routinely available. Mechanical ventilation for cancer patients with respiratory failure is an obvious target for limitation, if not elimination, by third-party payers and/or the government. Medical professionals need to provide guidance and leadership for cancer patients and their families when considering mechanical ventilation. Furthermore, they must be actively involved in determining guidelines for the fair, ethical allocation of critical care resources.

Further work is needed with respect to predicting outcomes for mechanically ventilated cancer patients, but this study represents an important step. It is appropriate for physicians to provide aggressive supportive care for critically ill patients with respiratory failure, although routinely providing mechanical ventilation to cancer patients may be inappropriately aggressive. The decision should be made on an individual basis. This model can help physicians caring for cancer patients in their discussions with colleagues and with patients and their families.

	ACKNOWLEDGMENTS

 
Supported by Memorial Sloan-Kettering Cancer Center.

We thank participating institutions for providing resources for site-specific data collection.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
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Submitted May 11, 1998; accepted November 3, 1998.

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This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Groeger, J. S. Articles by Price, K. Search for Related Content PubMed PubMed Citation Articles by Groeger, J. S. Articles by Price, K. Social Bookmarking                            What's this?