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Outcomes of elderly patients with stage IIIB–IV non-small cell lung cancer admitted to the intensive care unit
Lung Cancer 77 (2012) 600–604
Contents lists available at SciVerse ScienceDirect
Lung Cancer journal homepage: www.elsevier.com/locate/lungcan
Outcomes of elderly patients with stage IIIB–IV non-small cell lung cancer admitted to the intensive care unit Marcelo R. Bonomi a,b , Cardinale B. Smith a,b,∗ , Grace Mhango c , Juan P. Wisnivesky c,d a
Divisions of Hematology-Oncology, Mount Sinai School of Medicine, New York, NY, USA Divisions of Palliative Medicine, Mount Sinai School of Medicine, New York, NY, USA Divisions of General Internal Medicine, Mount Sinai School of Medicine, New York, NY, USA d Divisions of Pulmonary, Critical Care, and Sleep Medicine, Mount Sinai School of Medicine, New York, NY, USA b c
a r t i c l e
i n f o
Article history: Received 5 December 2011 Received in revised form 15 May 2012 Accepted 17 May 2012 Keywords: Elderly Intensive care unit Lung cancer Mortality
a b s t r a c t Background: Although the prognosis of elderly patients with stage IIIB and IV non-small cell lung cancer (NSCLC) is poor, it remains a common cause of cancer related admissions to the intensive care unit (ICU). The objective was to evaluate short and long-term outcomes of a population-based sample of elderly patients with advanced NSCLC who require ICU care. Methods: Using combined data from the Surveillance, Epidemiology and End Results registry and Medicare files, we identified 1134 patients >65 years of age with stage IIIB and IV NSCLC admitted to an ICU with a diagnosis of respiratory, cardiac, or neurologic complications, renal failure, or sepsis. We assessed rates and predictors of death during hospitalization. The Kaplan–Meier method was used to estimate mortality rates at 90 days and 1 year post hospital discharge. Results: In-hospital mortality was 33% (95% CI: 30–36%). The 90-day and 1-year mortality rate was 71% and 90%, respectively. Patients with an admitting diagnosis of sepsis had the highest rate of in-hospital mortality (59%). Of those who were alive at discharge, 52% were transferred to a skilled nursing facility, 6% to hospice, and 42% returned home. Conclusion: We found that one-third of elderly patients with advanced NSCLC admitted to the ICU do not survive hospitalization. Among survivors, most patients required continued institutionalization with a very low likelihood of surviving >1 year from discharge. This data should help patients, families, and health care providers of elderly patients with advanced NSCLC make decisions regarding ICU utilization. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Lung cancer is predominately a disease of the elderly and is also the leading cause of cancer-related mortality in both men and women in the United States (US). When lung cancer is diagnosed at an early stage, treatment with surgical resection is potentially curative. Unfortunately, >50% of patients with non small cell lung cancer (NSCLC) are diagnosed at an advanced stage which is not amenable to resection [1]. Although there have been recent advances in therapy, the overall 5-year survival for these patients remains <5% [2] with the majority of patients dying within two years of diagnosis [3]. Despite this poor prognosis, lung cancer is the third most common solid tumor in critically ill patients [4] and accounts for about 16% of all cancer admissions to the intensive care unit (ICU) [5].
∗ Corresponding author at: Division of Hematology/Medical Oncology, Tisch Cancer Institute, Hertzberg Palliative Care Institute, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1079, New York, NY 10029, USA. Tel.: +1 212 659 5627; fax: +1 646 537 8698. E-mail address: [email protected] (C.B. Smith). 0169-5002/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.lungcan.2012.05.103
The prognosis and long-term outcomes of lung cancer patients admitted to the ICU remains unclear. Older studies have shown that lung cancer patients have a high in-hospital mortality (75–95%) when admitted to the ICU [6–8]. However, more recent studies have reported considerably more favorable outcomes [9–12]. Most of these studies however, were conducted in tertiary referral centers, included patients with early and advanced stage, and were not focused on the elderly. ICU use in elderly patients with advanced NSCLC appears to be increasing [13]. As such, there is an increasing need for outcomes data in order for elderly patients, families, and physicians to make informed decisions about ICU admissions. In this study, we used data from the Surveillance, Epidemiology and End Results (SEER) registry linked to Medicare files, a nationally representative, population-based source of cancer data to assess the short and long-term outcomes of elderly patients with stage IIIB and IV NSCLC admitted to the ICU. 2. Methods Study patients were identified from the SEER-Medicare registry [14]. The SEER program collects data on all incident cancer
M.R. Bonomi et al. / Lung Cancer 77 (2012) 600–604
cases in selected areas of the US, covering approximately 26% of the US population [15]. For patient’s ≥ 65 years of age, SEER data has been linked to inpatient, outpatient, and physician Medicare claims. Using Medicare inpatient files we selected all patients > 65 years of age with a primary diagnosis of stage IIIB and IV NSCLC diagnosed between 1992 and 2005 with at least one admission to the medical ICU. To avoid including conditions that were potentially reversible and/or unlikely to be related to lung cancer (such as post-operative care, gastrointestinal bleed, or acute coronary syndromes), we limited our analysis to five conditions or complications which are common reasons for ICU admission among patients with advanced lung cancer and are likely related to disease progression. Thus, the study cohort was limited to patients admitted to the ICU due to the following conditions and diagnosis-related hospital billing (DRG) codes: respiratory problems (pulmonary embolism, pneumonia, chronic obstructive lung disease, respiratory failure, pulmonary edema, other respiratory conditions; DRG codes 78–80, 85–88, 96, 97,and 99–102); cardiac diseases (heart failure, cardiogenic shock, and cardiac arrest; DRG codes 127, 129, 138, and 139), renal failure (DRG codes 316 and 317), neurological conditions (brain metastasis, cerebro-vascular accident, seizures, other neurological conditions; DRG codes 10, 11, 14–17, 23–25, 34, and 35), Sepsis (DRG code 416). If a patient had more than one ICU admission related to one of these complications, one of the episodes was selected at random and included in the analysis. The use of mechanical ventilation, a common marker of severity of illness in the ICU, was determined from the International Classification of Diseases, 9th edition-clinical modification (ICD-9-CM), procedure codes 96.7x and DRG code 475. Sociodemographic information including age, sex, race/ethnicity, marital status, and income was obtained from SEER and Medicare databases. To evaluate the burden of comorbidities, we used the Deyo adaptation of the Charlson comorbidity index, applying lung cancer-specific condition weights [16,17]. Data regarding tumor size, extension, and lymph node involvement, was obtained from SEER. Using this information, patients were classified according to the most recent tumor, node, and metastases staging criteria [18]. Histologic subtypes were classified into categories of adenocarcinoma, squamous cell carcinoma, large cell carcinoma, and other histologic type. Tumor histology is coded in SEER using the International Classification of Diseases for Oncology, 3rd edition [19]. Radiation therapy (RT) use was ascertained from SEER and Medicare claims. Patients were considered as having received RT if they were coded by SEER as having received external beam radiation or if Medicare inpatient, outpatient, or physician claims contained claims indicating RT use [20]. We identified patients treated with chemotherapy using data from Medicare files, applying validated algorithms [21]. The main study outcome, death during hospitalization, was determined using data reported in the inpatient Medicare file. Site of placement at the time of discharge (home, skilled nursing facility, or hospice) for patients who survived hospitalization is also provided by Medicare as part of the inpatient file. Survival time was calculated as the interval from the date of hospital admission to the Medicare date of death. Those surviving past December 31, 2007 (alive at the end of follow-up) were classified as censored.
3. Statistical analysis Differences in the baseline characteristics between patients who survived and did not survive to hospital discharge were assessed using the Chi-square test. The probability of in-hospital mortality as well as mortality rates among patients with respiratory, cardiac, or neurological conditions, sepsis, and renal failure are reported
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with 95% confidence intervals based on the binomial distribution. We used the Kaplan–Meier method to estimate mortality rates at 90 days and 1 year after hospital discharge. The log-rank test was used to compare post discharge survival according to admission diagnosis and lung cancer stage. We used logistic regression analysis to identify independent predictors of death during hospitalization while adjusting for age, marital status, co-morbidity, race, stage, histology, pre-admission cancer treatment, and admission complication. Secondary analysis was performed to estimate differences in mortality rates at 90 days and 1 year after hospital discharge between earlier and later time periods (1992–1998 and 1999–2005). Variable testing was conducted using the likelihood ratio test. All analyses were performed with SAS statistical software (SAS, Nary, NC) and using two-sided p-values. 4. Results A total of 1134 patients with stage IIIB and IV were identified from the SEER-Medicare registry. Overall, 376 (33%, 95% CI: 30–36%) patients died during the hospitalization. Of the patients surviving hospitalization, 307 (42%) were discharged home, 384 (52%) to a skilled nursing facility and 48 (6%) to hospice. Only 143 (19%) of patients received some form of lung cancer directed treatment (chemotherapy and/or RT) after hospital discharge. Baseline characteristics of study patients are shown in Table 1. There was no difference in age (p = 0.82), sex (p = 0.72), race/ethnicity (p = 0.36), marital status (p = 0.70), income (p = 0.14), cancer stage (p = 0.79), tumor histology (p = 0.59), type of anticancer treatment prior to admission (p = 0.19), and comorbidities (p = 0.64) among patients who did or did not survive hospitalization. Patients who did not survive hospitalization were more likely to require mechanical ventilation (26% vs. 8%; p < 0.0001). The conditions related to the ICU admissions were respiratory in 36% of cases followed by cardiac disease (25%), sepsis (19%), neurological conditions (16%), and renal failure (4%). Overall, long-term survival following discharge among patients who survived hospitalization was very poor (Table 2). The all cause 90-day mortality rate was 71% with the lowest rates among patients with an ICU diagnosis of cardiac complications (59%; 95% CI: 53–65%). The highest 90-day mortality rates were observed among patients admitted with sepsis (86%; 95% CI: 81–90%) and those requiring mechanical ventilation (85%; 95% CI: 79–90%). Similarly, 1-year mortality was 90% across all ICU diagnoses and 97% (95% CI: 92–99%) for patients requiring mechanical ventilation. Secondary analysis stratified by stage showed that intra-hospital as well as 90-day and 1-year mortality were relatively similar among patients with stage IIIB and IV disease. On multivariate analysis, admissions related to respiratory conditions (odds ratio [OR]: 2.34; 95% CI: 1.43–3.82), sepsis (OR: 5.06; 95% CI: 3.04–8.43), renal failure (OR: 2.28; 95% CI: 1.02–5.10) and the need for mechanical ventilation (OR: 4.69; 95% CI: 3.02–7.30) were independent predictors of death during hospitalization. Secondary analysis stratified by time periods (1992–1998 and 1998–2005) did not demonstrate a difference in 90-day or 1-year mortality between the two time periods. The 90-day mortality was 69% (95% CI: 64–73%) for the earlier time period and 73% (95% CI: 69–76%) for the later time period. Similarly, the 1-year mortality was 91% (95% CI: 88–94%) for the earlier time period and 90% (95% CI: 88–92%) for the later time period. Similarly, multivariate analysis showed no interactions between risk factors for death and time period. 5. Discussion Despite the poor long-term outcomes of patients with advanced stage NSCLC and the uncertain benefit of the use of critical
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Table 1 Baseline characteristics of patients with stage IIIB and IV non-small cell lung cancer admitted to the intensive care unit. Characteristic Age, in years, n (%) 65–69 70–74 75–79 ≥80 Sex, n (%) Male Race/ethnicity, n (%) White Black Hispanic Other Marital status, n (%) Married Income quartiles, n (%) First Second Third Fourth Cancer stage, n (%) IIIB IV Histology, n (%) Adenocarcinoma Squamous cell carcinoma Large cell carcinoma Other Treatment prior to admission, n (%) No treatment Chemotherapy only Radiation only Chemotherapy and RT Comorbidities (NCI weighted score), n (%) <1 1–2 >2 1
Did not survive hospitalization N = 376
Survived hospitalization N = 758
p-Value
100 (27) 126 (33) 86 (23) 64 (17)
221 (29) 250 (33) 167 (22) 120 (16)
0.83
222 (59)
456 (60)
0.72
290 (77) 32 (9) 19 (5) 34 (9)
593 (78) 74 (10) 43 (6) 48 (6)
0.36
221 (60)
443 (61)
0.70
104 (28) 86 (23) 92 (24) 94 (25)
248 (33) 176 (23) 185 (24) 149 (20)
0.14
169 (45) 207 (55)
347 (46) 411 (54)
0.79
168 (45) 115 (30) 36 (10) 57 (15)
347 (46) 250 (33) 61 (8) 100 (13)
0.59
103 (27) 65 (17) 86 (23) 122 (33)
251 (33) 116 (15) 177 (24) 214 (28)
0.19
148 (44) 128 (38) 59 (18)
312 (47) 235 (36) 114 (17)
0.64
First indicates higher income quartile.
care resources in this patient population, ICU admissions remain common. Using population-based data we found that in-hospital mortality of elderly patients admitted to the ICU with advanced NSCLC is approximately 33%, but varies according to the underlying admission diagnosis. However, the long-term prognosis remains very poor and less than half of surviving patients return to their homes. These data should help guide decisions regarding use of the ICU among elderly patients with advanced NSCLC. Future efforts should be focused on trying to further elucidate which subgroup of patients with advanced NSCLC derive the most benefit from the intensive care provided in ICU settings.
Several single institution, retrospective studies have reported results of in-hospital mortality rates in patients admitted to the ICU with lung cancer [6–10,12,22]. In these older series, in-hospital mortality rate was very high with very few patients surviving hospitalization [6–8]. More recent studies have demonstrated more favorable in-hospital mortality [9,10,12,22]. Roques et al. reported an in-hospital mortality rate of 54% with a 6-month mortality rate of 75% [10]. Similarly, a study with a higher percentage (60%) of patients with advanced stage lung cancer showed a more favorable in-hospital mortality rate of 40% [22]. However, these studies were limited to single, mostly tertiary institutions, included
Table 2 Survival outcomes of patients with stage IIIB and IV non-small cell lung cancer admitted to the intensive care unit. Admission diagnosis Outcomes All stages Did not survive hospitalization, n (%) 90-day mortalitya (95% CI) 1-year mortality (95% CI) Stage IIIB Did not survive hospitalization, n (%) 90-day mortality (95% CI) 1-year mortality (95% CI) Stage IV Did not survive hospitalization, n (%) 90-day mortality (95% CI) 1-year mortality (95% CI)
CNS N = 187
Respiratory N = 406
Cardiac N = 281
43 (23) 71 (64–77) 93 (89–96)
130 (32) 73 (69–77) 89 (86–92)
61 (22) 59 (53–65) 86 (82–90)
16 (36) 71 (58–83) 87 (75–95)
126 (59) 86 (81–90) 97 (94–99)
15 (32) 73 (61–85) 90 (80–96)
67 (32) 70 (64–76) 88 (83–92)
30 (20) 53 (45–61) 79 (73–85)
2 (13) 47 (26–74) 73 (50–92)
55 (61) 84 (76–91) 98 (93–100)
28 (20) 70 (62–77) 94 (89–97)
63 (32) 77 (71–82) 90 (86–94)
31 (24) 66 (58–74) 95 (90–98)
14 (47) 83 (68–94) 93 (81–99)
71 (57) 86 (80–92) 96 (92–99)
CNS denotes central nervous system, CI denotes confidence interval. a Estimated using the Kaplan–Meier method.
Renal N = 45
Sepsis N = 215
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different age groups, as well as heterogenous populations in terms of cancer stage. Although our results only reflect data until 2005, it is still very consistent with contemporary studies [10,23]. However, our analyses stratifying and adjusting for year of admission did not show significant time trends in ICU mortality rates among the conditions studied. Our results extend the findings of these recent analyses by showing, in a population-based sample, that approximately one-third of elderly patients with advanced NSCLC admitted to the ICU die during hospitalization. Extended followup data also allowed us to show that long-term outcomes of these patients remain very poor despite the reduced in-hospital mortality rates. The reasons for improved short-term outcomes of lung cancer patients admitted to the ICU in this and other more recent studies is not entirely clear. It has been speculated that improvements in the therapeutic strategies employed in ICUs (such as newer mechanical ventilation modalities and better management of sepsis) may explain these findings [12]. Alternatively, higher rates of survival at hospital discharge may be related to changes in the characteristics of cancer patients admitted to the ICU over time or selection of patients who are more likely to benefit from ICU admission. Although our data suggests worse long-term prognosis than previously reported, our patient population reflects elderly patients with advanced disease, a subgroup of patients who are less likely to experience a benefit from ICU care. Several studies have attempted to identify the predictors of poor ICU outcomes that may help select patients who are least likely to benefit from ICU care [10,11,24–26]. These studies have shown that sepsis, respiratory failure requiring mechanical ventilation, failure of two or more organ systems, and a poor performance status are independently associated with worse short and longterm outcomes. However, risk factors were not consistent across studies. We also found in multivariate analysis that an admission diagnosis of sepsis, renal failure, or respiratory conditions, and the need for mechanical ventilation are independent predictors of in-hospital mortality among patients with lung cancer. This information may be useful for physicians and family members when confronting decisions regarding discontinuation of high intensity care for advanced-stage elderly patients who develop respiratory failure while admitted to the ICU. The SEER-Medicare database however, does not contain data about severity of disease at admission or results of laboratory tests. Thus, we were not able to assess whether it may be possible to further identify patients at risk for worse outcomes based on these data. Another important clinical endpoint in assessing outcomes for this patient population relates to the disposition of patients after an ICU admission. A prior analysis of trends in the use of ICUs at the end of life found that 57% of patients who survive hospitalization are discharged home versus 43% to an institutional setting [13]. Additionally, slightly less than half of those patients discharged home were eventually enrolled in hospice care [13]. In our study, more than half (52%) of patients were discharged to an institutional setting which suggests that these patients had significant impairments that prevented them from being able to return to their previous level of functioning. Our finding that only 19% of patients who survived an ICU admission received some type of anticancer directed therapy (chemotherapy and/or radiation therapy) also supports the conclusion that the medical status of these elderly patients were considerably compromised after discharge. The low rate of hospice utilization at discharge is consistent with other reports suggesting under use of potentially beneficial palliative care services [27,28]. There are several strengths and weaknesses of this study that should be noted. This is a population based sample of advanced lung cancer patients who were admitted to multiple ICUs in several regions of the US. Thus, the generalizability of our findings should
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be strong. In order to have access to detailed information provided by Medicare, our sample was limited to patients >65 years of age; thus our results cannot be generalized to younger patients with advanced NSCLC. However, this information is important because >50% of lung cancer patients are >65 years of age and older cancer patients may be less likely to survive an episode of ICU admission due to co-morbid conditions and poorer functional reserve. Additionally, we excluded patients who were admitted to the ICU with other conditions such as gastrointestinal bleeding or acute coronary syndromes, conditions which are less likely to be associated with uncontrolled lung cancer or cancer progression. This design may have excluded patients with a better prognosis. However, in this elderly population with a high rate co-morbidities we were unable to distinguish whether other conditions such as gastrointestinal bleeding or acute coronary syndromes were related to cancer-treatments (for example, the use of corticosteroids with chemotherapy) or underlying medical problems. Additionally, these conditions are potentially reversible and may be more amenable to intervention. Thus, there is less controversy about the potential value of ICU support in this setting to stabilize the patient. We did not have information regarding patient performance status, tumor progression, severity of illness, or details about the ICU course (i.e. laboratory test results, use of dialysis, etc.), factors that may be associated with in-hospital mortality rates. Although SEER-Medicare does not contain information regarding patient performance status, we did use the Charlson comorbidity index to evaluate the burdens of patient’s comorbidities. Although the number of comorbid conditions is not equivalent to functional status, it has been associated with the likelihood of receiving treatment in other cancers [29,30]. In conclusion, our data shows that approximately a third of elderly patients with advanced stage NSCLC admitted to the ICU do not survive to hospital discharge. Moreover, long-term survival of this population is very poor with approximately 10% of patients alive at one year. This data is useful and can assist with making informed decision making about the use of ICU resources for these patients. Further research is necessary to determine which patients benefit from this costly and scarce resource.
Funding This work was supported in part by a Research Supplement to Promote Diversity in Health-Related Research Program Award Number [R01CA131348] from the National Cancer Institute.
Conflict of interest Dr. Wisnivesky is a member of the research board of EHE International, has received lecture fees from Novartis Pharmaceutical, consulting honorarium from UBC, and a research grant from GlaxoSmithKline. The remaining authors have no relevant relationships to disclose.
Acknowledgements This study used the linked SEER-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the Applied Research Program, NCI; the Office of Research, Development and Information, CMS; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database.
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Contents lists available at SciVerse ScienceDirect
Lung Cancer journal homepage: www.elsevier.com/locate/lungcan
Outcomes of elderly patients with stage IIIB–IV non-small cell lung cancer admitted to the intensive care unit Marcelo R. Bonomi a,b , Cardinale B. Smith a,b,∗ , Grace Mhango c , Juan P. Wisnivesky c,d a
Divisions of Hematology-Oncology, Mount Sinai School of Medicine, New York, NY, USA Divisions of Palliative Medicine, Mount Sinai School of Medicine, New York, NY, USA Divisions of General Internal Medicine, Mount Sinai School of Medicine, New York, NY, USA d Divisions of Pulmonary, Critical Care, and Sleep Medicine, Mount Sinai School of Medicine, New York, NY, USA b c
a r t i c l e
i n f o
Article history: Received 5 December 2011 Received in revised form 15 May 2012 Accepted 17 May 2012 Keywords: Elderly Intensive care unit Lung cancer Mortality
a b s t r a c t Background: Although the prognosis of elderly patients with stage IIIB and IV non-small cell lung cancer (NSCLC) is poor, it remains a common cause of cancer related admissions to the intensive care unit (ICU). The objective was to evaluate short and long-term outcomes of a population-based sample of elderly patients with advanced NSCLC who require ICU care. Methods: Using combined data from the Surveillance, Epidemiology and End Results registry and Medicare files, we identified 1134 patients >65 years of age with stage IIIB and IV NSCLC admitted to an ICU with a diagnosis of respiratory, cardiac, or neurologic complications, renal failure, or sepsis. We assessed rates and predictors of death during hospitalization. The Kaplan–Meier method was used to estimate mortality rates at 90 days and 1 year post hospital discharge. Results: In-hospital mortality was 33% (95% CI: 30–36%). The 90-day and 1-year mortality rate was 71% and 90%, respectively. Patients with an admitting diagnosis of sepsis had the highest rate of in-hospital mortality (59%). Of those who were alive at discharge, 52% were transferred to a skilled nursing facility, 6% to hospice, and 42% returned home. Conclusion: We found that one-third of elderly patients with advanced NSCLC admitted to the ICU do not survive hospitalization. Among survivors, most patients required continued institutionalization with a very low likelihood of surviving >1 year from discharge. This data should help patients, families, and health care providers of elderly patients with advanced NSCLC make decisions regarding ICU utilization. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Lung cancer is predominately a disease of the elderly and is also the leading cause of cancer-related mortality in both men and women in the United States (US). When lung cancer is diagnosed at an early stage, treatment with surgical resection is potentially curative. Unfortunately, >50% of patients with non small cell lung cancer (NSCLC) are diagnosed at an advanced stage which is not amenable to resection [1]. Although there have been recent advances in therapy, the overall 5-year survival for these patients remains <5% [2] with the majority of patients dying within two years of diagnosis [3]. Despite this poor prognosis, lung cancer is the third most common solid tumor in critically ill patients [4] and accounts for about 16% of all cancer admissions to the intensive care unit (ICU) [5].
∗ Corresponding author at: Division of Hematology/Medical Oncology, Tisch Cancer Institute, Hertzberg Palliative Care Institute, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1079, New York, NY 10029, USA. Tel.: +1 212 659 5627; fax: +1 646 537 8698. E-mail address: [email protected] (C.B. Smith). 0169-5002/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.lungcan.2012.05.103
The prognosis and long-term outcomes of lung cancer patients admitted to the ICU remains unclear. Older studies have shown that lung cancer patients have a high in-hospital mortality (75–95%) when admitted to the ICU [6–8]. However, more recent studies have reported considerably more favorable outcomes [9–12]. Most of these studies however, were conducted in tertiary referral centers, included patients with early and advanced stage, and were not focused on the elderly. ICU use in elderly patients with advanced NSCLC appears to be increasing [13]. As such, there is an increasing need for outcomes data in order for elderly patients, families, and physicians to make informed decisions about ICU admissions. In this study, we used data from the Surveillance, Epidemiology and End Results (SEER) registry linked to Medicare files, a nationally representative, population-based source of cancer data to assess the short and long-term outcomes of elderly patients with stage IIIB and IV NSCLC admitted to the ICU. 2. Methods Study patients were identified from the SEER-Medicare registry [14]. The SEER program collects data on all incident cancer
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cases in selected areas of the US, covering approximately 26% of the US population [15]. For patient’s ≥ 65 years of age, SEER data has been linked to inpatient, outpatient, and physician Medicare claims. Using Medicare inpatient files we selected all patients > 65 years of age with a primary diagnosis of stage IIIB and IV NSCLC diagnosed between 1992 and 2005 with at least one admission to the medical ICU. To avoid including conditions that were potentially reversible and/or unlikely to be related to lung cancer (such as post-operative care, gastrointestinal bleed, or acute coronary syndromes), we limited our analysis to five conditions or complications which are common reasons for ICU admission among patients with advanced lung cancer and are likely related to disease progression. Thus, the study cohort was limited to patients admitted to the ICU due to the following conditions and diagnosis-related hospital billing (DRG) codes: respiratory problems (pulmonary embolism, pneumonia, chronic obstructive lung disease, respiratory failure, pulmonary edema, other respiratory conditions; DRG codes 78–80, 85–88, 96, 97,and 99–102); cardiac diseases (heart failure, cardiogenic shock, and cardiac arrest; DRG codes 127, 129, 138, and 139), renal failure (DRG codes 316 and 317), neurological conditions (brain metastasis, cerebro-vascular accident, seizures, other neurological conditions; DRG codes 10, 11, 14–17, 23–25, 34, and 35), Sepsis (DRG code 416). If a patient had more than one ICU admission related to one of these complications, one of the episodes was selected at random and included in the analysis. The use of mechanical ventilation, a common marker of severity of illness in the ICU, was determined from the International Classification of Diseases, 9th edition-clinical modification (ICD-9-CM), procedure codes 96.7x and DRG code 475. Sociodemographic information including age, sex, race/ethnicity, marital status, and income was obtained from SEER and Medicare databases. To evaluate the burden of comorbidities, we used the Deyo adaptation of the Charlson comorbidity index, applying lung cancer-specific condition weights [16,17]. Data regarding tumor size, extension, and lymph node involvement, was obtained from SEER. Using this information, patients were classified according to the most recent tumor, node, and metastases staging criteria [18]. Histologic subtypes were classified into categories of adenocarcinoma, squamous cell carcinoma, large cell carcinoma, and other histologic type. Tumor histology is coded in SEER using the International Classification of Diseases for Oncology, 3rd edition [19]. Radiation therapy (RT) use was ascertained from SEER and Medicare claims. Patients were considered as having received RT if they were coded by SEER as having received external beam radiation or if Medicare inpatient, outpatient, or physician claims contained claims indicating RT use [20]. We identified patients treated with chemotherapy using data from Medicare files, applying validated algorithms [21]. The main study outcome, death during hospitalization, was determined using data reported in the inpatient Medicare file. Site of placement at the time of discharge (home, skilled nursing facility, or hospice) for patients who survived hospitalization is also provided by Medicare as part of the inpatient file. Survival time was calculated as the interval from the date of hospital admission to the Medicare date of death. Those surviving past December 31, 2007 (alive at the end of follow-up) were classified as censored.
3. Statistical analysis Differences in the baseline characteristics between patients who survived and did not survive to hospital discharge were assessed using the Chi-square test. The probability of in-hospital mortality as well as mortality rates among patients with respiratory, cardiac, or neurological conditions, sepsis, and renal failure are reported
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with 95% confidence intervals based on the binomial distribution. We used the Kaplan–Meier method to estimate mortality rates at 90 days and 1 year after hospital discharge. The log-rank test was used to compare post discharge survival according to admission diagnosis and lung cancer stage. We used logistic regression analysis to identify independent predictors of death during hospitalization while adjusting for age, marital status, co-morbidity, race, stage, histology, pre-admission cancer treatment, and admission complication. Secondary analysis was performed to estimate differences in mortality rates at 90 days and 1 year after hospital discharge between earlier and later time periods (1992–1998 and 1999–2005). Variable testing was conducted using the likelihood ratio test. All analyses were performed with SAS statistical software (SAS, Nary, NC) and using two-sided p-values. 4. Results A total of 1134 patients with stage IIIB and IV were identified from the SEER-Medicare registry. Overall, 376 (33%, 95% CI: 30–36%) patients died during the hospitalization. Of the patients surviving hospitalization, 307 (42%) were discharged home, 384 (52%) to a skilled nursing facility and 48 (6%) to hospice. Only 143 (19%) of patients received some form of lung cancer directed treatment (chemotherapy and/or RT) after hospital discharge. Baseline characteristics of study patients are shown in Table 1. There was no difference in age (p = 0.82), sex (p = 0.72), race/ethnicity (p = 0.36), marital status (p = 0.70), income (p = 0.14), cancer stage (p = 0.79), tumor histology (p = 0.59), type of anticancer treatment prior to admission (p = 0.19), and comorbidities (p = 0.64) among patients who did or did not survive hospitalization. Patients who did not survive hospitalization were more likely to require mechanical ventilation (26% vs. 8%; p < 0.0001). The conditions related to the ICU admissions were respiratory in 36% of cases followed by cardiac disease (25%), sepsis (19%), neurological conditions (16%), and renal failure (4%). Overall, long-term survival following discharge among patients who survived hospitalization was very poor (Table 2). The all cause 90-day mortality rate was 71% with the lowest rates among patients with an ICU diagnosis of cardiac complications (59%; 95% CI: 53–65%). The highest 90-day mortality rates were observed among patients admitted with sepsis (86%; 95% CI: 81–90%) and those requiring mechanical ventilation (85%; 95% CI: 79–90%). Similarly, 1-year mortality was 90% across all ICU diagnoses and 97% (95% CI: 92–99%) for patients requiring mechanical ventilation. Secondary analysis stratified by stage showed that intra-hospital as well as 90-day and 1-year mortality were relatively similar among patients with stage IIIB and IV disease. On multivariate analysis, admissions related to respiratory conditions (odds ratio [OR]: 2.34; 95% CI: 1.43–3.82), sepsis (OR: 5.06; 95% CI: 3.04–8.43), renal failure (OR: 2.28; 95% CI: 1.02–5.10) and the need for mechanical ventilation (OR: 4.69; 95% CI: 3.02–7.30) were independent predictors of death during hospitalization. Secondary analysis stratified by time periods (1992–1998 and 1998–2005) did not demonstrate a difference in 90-day or 1-year mortality between the two time periods. The 90-day mortality was 69% (95% CI: 64–73%) for the earlier time period and 73% (95% CI: 69–76%) for the later time period. Similarly, the 1-year mortality was 91% (95% CI: 88–94%) for the earlier time period and 90% (95% CI: 88–92%) for the later time period. Similarly, multivariate analysis showed no interactions between risk factors for death and time period. 5. Discussion Despite the poor long-term outcomes of patients with advanced stage NSCLC and the uncertain benefit of the use of critical
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Table 1 Baseline characteristics of patients with stage IIIB and IV non-small cell lung cancer admitted to the intensive care unit. Characteristic Age, in years, n (%) 65–69 70–74 75–79 ≥80 Sex, n (%) Male Race/ethnicity, n (%) White Black Hispanic Other Marital status, n (%) Married Income quartiles, n (%) First Second Third Fourth Cancer stage, n (%) IIIB IV Histology, n (%) Adenocarcinoma Squamous cell carcinoma Large cell carcinoma Other Treatment prior to admission, n (%) No treatment Chemotherapy only Radiation only Chemotherapy and RT Comorbidities (NCI weighted score), n (%) <1 1–2 >2 1
Did not survive hospitalization N = 376
Survived hospitalization N = 758
p-Value
100 (27) 126 (33) 86 (23) 64 (17)
221 (29) 250 (33) 167 (22) 120 (16)
0.83
222 (59)
456 (60)
0.72
290 (77) 32 (9) 19 (5) 34 (9)
593 (78) 74 (10) 43 (6) 48 (6)
0.36
221 (60)
443 (61)
0.70
104 (28) 86 (23) 92 (24) 94 (25)
248 (33) 176 (23) 185 (24) 149 (20)
0.14
169 (45) 207 (55)
347 (46) 411 (54)
0.79
168 (45) 115 (30) 36 (10) 57 (15)
347 (46) 250 (33) 61 (8) 100 (13)
0.59
103 (27) 65 (17) 86 (23) 122 (33)
251 (33) 116 (15) 177 (24) 214 (28)
0.19
148 (44) 128 (38) 59 (18)
312 (47) 235 (36) 114 (17)
0.64
First indicates higher income quartile.
care resources in this patient population, ICU admissions remain common. Using population-based data we found that in-hospital mortality of elderly patients admitted to the ICU with advanced NSCLC is approximately 33%, but varies according to the underlying admission diagnosis. However, the long-term prognosis remains very poor and less than half of surviving patients return to their homes. These data should help guide decisions regarding use of the ICU among elderly patients with advanced NSCLC. Future efforts should be focused on trying to further elucidate which subgroup of patients with advanced NSCLC derive the most benefit from the intensive care provided in ICU settings.
Several single institution, retrospective studies have reported results of in-hospital mortality rates in patients admitted to the ICU with lung cancer [6–10,12,22]. In these older series, in-hospital mortality rate was very high with very few patients surviving hospitalization [6–8]. More recent studies have demonstrated more favorable in-hospital mortality [9,10,12,22]. Roques et al. reported an in-hospital mortality rate of 54% with a 6-month mortality rate of 75% [10]. Similarly, a study with a higher percentage (60%) of patients with advanced stage lung cancer showed a more favorable in-hospital mortality rate of 40% [22]. However, these studies were limited to single, mostly tertiary institutions, included
Table 2 Survival outcomes of patients with stage IIIB and IV non-small cell lung cancer admitted to the intensive care unit. Admission diagnosis Outcomes All stages Did not survive hospitalization, n (%) 90-day mortalitya (95% CI) 1-year mortality (95% CI) Stage IIIB Did not survive hospitalization, n (%) 90-day mortality (95% CI) 1-year mortality (95% CI) Stage IV Did not survive hospitalization, n (%) 90-day mortality (95% CI) 1-year mortality (95% CI)
CNS N = 187
Respiratory N = 406
Cardiac N = 281
43 (23) 71 (64–77) 93 (89–96)
130 (32) 73 (69–77) 89 (86–92)
61 (22) 59 (53–65) 86 (82–90)
16 (36) 71 (58–83) 87 (75–95)
126 (59) 86 (81–90) 97 (94–99)
15 (32) 73 (61–85) 90 (80–96)
67 (32) 70 (64–76) 88 (83–92)
30 (20) 53 (45–61) 79 (73–85)
2 (13) 47 (26–74) 73 (50–92)
55 (61) 84 (76–91) 98 (93–100)
28 (20) 70 (62–77) 94 (89–97)
63 (32) 77 (71–82) 90 (86–94)
31 (24) 66 (58–74) 95 (90–98)
14 (47) 83 (68–94) 93 (81–99)
71 (57) 86 (80–92) 96 (92–99)
CNS denotes central nervous system, CI denotes confidence interval. a Estimated using the Kaplan–Meier method.
Renal N = 45
Sepsis N = 215
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different age groups, as well as heterogenous populations in terms of cancer stage. Although our results only reflect data until 2005, it is still very consistent with contemporary studies [10,23]. However, our analyses stratifying and adjusting for year of admission did not show significant time trends in ICU mortality rates among the conditions studied. Our results extend the findings of these recent analyses by showing, in a population-based sample, that approximately one-third of elderly patients with advanced NSCLC admitted to the ICU die during hospitalization. Extended followup data also allowed us to show that long-term outcomes of these patients remain very poor despite the reduced in-hospital mortality rates. The reasons for improved short-term outcomes of lung cancer patients admitted to the ICU in this and other more recent studies is not entirely clear. It has been speculated that improvements in the therapeutic strategies employed in ICUs (such as newer mechanical ventilation modalities and better management of sepsis) may explain these findings [12]. Alternatively, higher rates of survival at hospital discharge may be related to changes in the characteristics of cancer patients admitted to the ICU over time or selection of patients who are more likely to benefit from ICU admission. Although our data suggests worse long-term prognosis than previously reported, our patient population reflects elderly patients with advanced disease, a subgroup of patients who are less likely to experience a benefit from ICU care. Several studies have attempted to identify the predictors of poor ICU outcomes that may help select patients who are least likely to benefit from ICU care [10,11,24–26]. These studies have shown that sepsis, respiratory failure requiring mechanical ventilation, failure of two or more organ systems, and a poor performance status are independently associated with worse short and longterm outcomes. However, risk factors were not consistent across studies. We also found in multivariate analysis that an admission diagnosis of sepsis, renal failure, or respiratory conditions, and the need for mechanical ventilation are independent predictors of in-hospital mortality among patients with lung cancer. This information may be useful for physicians and family members when confronting decisions regarding discontinuation of high intensity care for advanced-stage elderly patients who develop respiratory failure while admitted to the ICU. The SEER-Medicare database however, does not contain data about severity of disease at admission or results of laboratory tests. Thus, we were not able to assess whether it may be possible to further identify patients at risk for worse outcomes based on these data. Another important clinical endpoint in assessing outcomes for this patient population relates to the disposition of patients after an ICU admission. A prior analysis of trends in the use of ICUs at the end of life found that 57% of patients who survive hospitalization are discharged home versus 43% to an institutional setting [13]. Additionally, slightly less than half of those patients discharged home were eventually enrolled in hospice care [13]. In our study, more than half (52%) of patients were discharged to an institutional setting which suggests that these patients had significant impairments that prevented them from being able to return to their previous level of functioning. Our finding that only 19% of patients who survived an ICU admission received some type of anticancer directed therapy (chemotherapy and/or radiation therapy) also supports the conclusion that the medical status of these elderly patients were considerably compromised after discharge. The low rate of hospice utilization at discharge is consistent with other reports suggesting under use of potentially beneficial palliative care services [27,28]. There are several strengths and weaknesses of this study that should be noted. This is a population based sample of advanced lung cancer patients who were admitted to multiple ICUs in several regions of the US. Thus, the generalizability of our findings should
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be strong. In order to have access to detailed information provided by Medicare, our sample was limited to patients >65 years of age; thus our results cannot be generalized to younger patients with advanced NSCLC. However, this information is important because >50% of lung cancer patients are >65 years of age and older cancer patients may be less likely to survive an episode of ICU admission due to co-morbid conditions and poorer functional reserve. Additionally, we excluded patients who were admitted to the ICU with other conditions such as gastrointestinal bleeding or acute coronary syndromes, conditions which are less likely to be associated with uncontrolled lung cancer or cancer progression. This design may have excluded patients with a better prognosis. However, in this elderly population with a high rate co-morbidities we were unable to distinguish whether other conditions such as gastrointestinal bleeding or acute coronary syndromes were related to cancer-treatments (for example, the use of corticosteroids with chemotherapy) or underlying medical problems. Additionally, these conditions are potentially reversible and may be more amenable to intervention. Thus, there is less controversy about the potential value of ICU support in this setting to stabilize the patient. We did not have information regarding patient performance status, tumor progression, severity of illness, or details about the ICU course (i.e. laboratory test results, use of dialysis, etc.), factors that may be associated with in-hospital mortality rates. Although SEER-Medicare does not contain information regarding patient performance status, we did use the Charlson comorbidity index to evaluate the burdens of patient’s comorbidities. Although the number of comorbid conditions is not equivalent to functional status, it has been associated with the likelihood of receiving treatment in other cancers [29,30]. In conclusion, our data shows that approximately a third of elderly patients with advanced stage NSCLC admitted to the ICU do not survive to hospital discharge. Moreover, long-term survival of this population is very poor with approximately 10% of patients alive at one year. This data is useful and can assist with making informed decision making about the use of ICU resources for these patients. Further research is necessary to determine which patients benefit from this costly and scarce resource.
Funding This work was supported in part by a Research Supplement to Promote Diversity in Health-Related Research Program Award Number [R01CA131348] from the National Cancer Institute.
Conflict of interest Dr. Wisnivesky is a member of the research board of EHE International, has received lecture fees from Novartis Pharmaceutical, consulting honorarium from UBC, and a research grant from GlaxoSmithKline. The remaining authors have no relevant relationships to disclose.
Acknowledgements This study used the linked SEER-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the Applied Research Program, NCI; the Office of Research, Development and Information, CMS; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database.
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