Abstract
Context
The use of targeted therapy at the end-of-life has not been well characterized.
Objectives
To determine the frequency and predictors of targeted therapy use in the last days of life.
Methods
All adult patients residing in the Houston area who died of advanced cancer between September 1, 2009 and February 28, 2010 and had contact with our institution within the last three months of life were included. We collected baseline demographics and data on chemotherapy and targeted agents.
Results
Eight hundred sixteen patients were included: average age 62 years (range 21–97), female 48% and White 61%. The median interval between the last treatment and death was 47 (interquartile range [IQR] 21–97) days for targeted agents and 57 (IQR 26–118) days for chemotherapeutic agents. Within the last 30 days of life, 116 (14%) patients received targeted agents and 147 (18%) received chemotherapy. Regimens given in the last 30 days of life included a median of one (IQR 1–2) chemotherapeutic/targeted agents, and 43 (5%) patients receiving targeted agents had concurrent chemotherapy. The most common targeted agents in the last 30 days of life were erlotinib (n=25), bevacizumab (n=20), rituximab (n=11), gemtuzumab (n=8) and temsirolimus (n=8). On multivariate analysis, younger age (odds ratio [OR] 0.98 per year, P=0.01), hematologic malignancy (OR=6.1, P < 0.001) and lung malignancy (OR=2.6, P=0.05) were associated with increased targeted agent use in the last 30 days of life.
Conclusion
Targeted agents were used as often as chemotherapy at the end of life, particularly among younger patients and those with hematologic malignancies. Guidelines on targeted therapy use at the end of life are needed.
Keywords: Anti-neoplastic agents, end of life, palliative care, quality of care, supportive care, targeted agents
Introduction
Our increased understanding of the molecular basis of cancer has resulted in an explosion in the number of targeted therapeutic options (1, 2). Targeted agents include a vast array of monoclonal antibodies, tyrosine kinase inhibitors and other biologics, and are now being routinely used in patient care, with many more under development (3). A majority of these agents are given, with a palliative intent, to patients with advanced cancer.
The use of targeted therapy at the end of life has not been well characterized. Multiple studies have examined the use of chemotherapy among patients with far advanced disease (4, 5). Chemotherapeutic agents are generally associated with significant toxicities and limited benefits when given to patients with poor performance status and/or survival. Thus, published literature considers the use of chemotherapy in the last two to four weeks of life a negative quality-of-care indicator (6–8).
To our knowledge, only two studies have examined the use of targeted agents at the end of life, one focusing on patients with lung cancer (9) and the other on patients admitted to an acute palliative care unit (10). A better understanding of the frequency of targeted agent use at the end of life, and the factors associated with their use, would potentially allow us to improve the quality of end-of-life care. In this retrospective study, we determined the frequency and predictors of targeted agent use in the last 30 days of life.
Methods
Study Setting and Eligibility Criteria
The Institutional Review Board approved this study, and waived the requirement of informed consent. All adult patients in the Houston area who died of advanced cancer between September 1, 2009 and February 28, 2010, and had contact with M. D. Anderson Cancer Center within the last three months of life were included in this study. Patients who transferred care to outside oncologists, relocated to another city or who were lost to follow-up were excluded. These criteria were chosen so that all patients were either under the direct care of M. D. Anderson Cancer Center or referred to a local hospice, and we were able to reliably capture their information at the end of life (11).
Data Collection
We collected baseline demographics, including age, sex, race, marital status, cancer diagnosis and date of advanced cancer diagnosis. Advanced cancer is defined as locally advanced, metastatic or recurrent disease not amenable to local therapy for solid tumors; advanced stage disease for chronic leukemias and low grade lymphomas; and recurrent disease for acute leukemias, high grade lymphomas and multiple myeloma.
Both chemotherapy and targeted agents, either standard and/or experimental regimens, are available for every tumor type at our institution. The medication name(s) and date of the last documented targeted/chemotherapeutic treatment received before death were retrieved from the electronic chart. Steroids and hormonal therapy was not examined.
Statistical Analysis
We summarized the baseline demographics using descriptive statistics, including means, medians, ranges, interquartile range (IQR) and frequencies. We compared the characteristics between patients who received targeted agents and those who did not receive targeted agents in the last 30 days of life using the t-test for continuous, normally distributed variables (e.g., age), the Mann-Whitney test for continuous, non-parametric variables (e.g., duration between advanced cancer diagnosis and death), and Pearson’s Chi-square test or Fisher’s exact test for categorical variables (e.g., race). We used a multivariate logistic regression model with backward elimination to identify factors associated with targeted and chemotherapeutic agent use in the last 30 days of life. Variables included in the model were age, sex, race, marital status, cancer diagnosis, and survival less than six months between advanced cancer diagnosis and death to account for an aggressive disease course. The same procedure was repeated for chemotherapy use in the last 30 days of life.
To compare the pattern of use between targeted therapy and chemotherapy, we used the McNemar test for binary variables (e.g., treatment within last 30 days of life) and the Wilcoxon test for continuous variables (e.g., median interval between last treatment and death). The Kaplan Meier method also was used to determine the median duration between last cancer treatment and death by cancer type. The log rank test was used to compare the intervals among various cancer types.
The Statistical Package for the Social Sciences (IBM SPSS version 19.0, SPSS Inc., Chicago, IL) software was used for statistical analysis. A P-value of <0.05 was considered significant.
Results
Patient Characteristics
Table 1 shows the baseline characteristics of the 816 decedents included in this study. Gastrointestinal and lung malignancies were the most common. The median interval between advanced cancer diagnosis and death was only 12 (IQR 5–25) months.
Table 1.
Patient Characteristics (N=816)
| Patient Characteristics | n (%)a |
|---|---|
| Age in years, mean (range) | 62 (21–97) |
| Female sex | 390 (48) |
| Race | |
| White | 499 (61) |
| Black | 178 (22) |
| Hispanic | 97 (12) |
| Asian | 32 (4) |
| Others | 10 (1) |
| Married | 504 (62) |
| Education | |
| High school or less | 284 (35) |
| College education | 256 (31) |
| Post-graduate education | 63 (8) |
| Not available | 213 (26) |
| Cancer type | |
| Breast | 71 (9) |
| Gastrointestinal | 178 (22) |
| Genitourinary | 89 (11) |
| Gynecologic | 61 (7) |
| Head and neck | 48 (6) |
| Hematologic | 113 (14) |
| Other | 94 (12) |
| Respiratory | 162 (20) |
| Months between advanced cancer diagnosis and death, median (interauartile range) |
12 (5–25) |
Column percentage unless otherwise specified.
Targeted and Chemotherapeutic Agent Use at the End of Life
Three hundred thirty-four (39%) patients with advanced cancer received targeted agents and 533 (65%) patients received chemotherapy during the course of their illness. The median interval between the last treatment and death was 47 (IQR 21–97) days for targeted agents and 57 (IQR 26–118) days for chemotherapeutic agents.
A total of 220 (27%) patients received targeted therapy and/or chemotherapy in the 30- day period prior to their death. Within the last 30 days of life, patients were more likely to be given chemotherapy than targeted agents (147 (18%) vs. 116 (14%), P=0.02); however, no significant difference was found for the last 14 days of life (64 (8%) vs. 56 (7%), P=0.45). The most commonly used targeted and chemotherapeutic agents are shown in Table 2. The use of targeted agents in the last 30 days of life was associated with chemotherapy use in the same period (P<0.001). Forty-three (5%) patients received both chemotherapy and targeted agents in the last 30 days of life.
Table 2.
Most Commonly Administered Targeted and Chemotherapeutic Agents in the Last 30 Days of Life
| Targeted Agents | Chemotherapeutic Agents | ||||
|---|---|---|---|---|---|
| Name | n | Approximate cost per month (US$)a |
Name | n | Approximate cost per month (US$)a |
| Erlotinib | 25 | 4823 | Gemcitabine | 21 | 5006 |
| Bevacizumab | 20 | 9379 | Cytarabine | 16 | 125 |
| Rituximab | 11 | 5746 | Cisplatin | 13 | 78 |
| Gemtuzumab | 8 | 19871 | Cyclophosphamide | 13 | 147 |
| Sorafenib | 8 | 7460 | Methotrexate | 12 | 8 |
| Temsirolimus | 8 | 5872 | 5-Fluorouracil | 10 | 65 |
| Bortezomib | 7 | 3998 | Capecitabine | 10 | 4858 |
| Cetuximab | 5 | 9907 | Paclitaxel | 10 | 161 |
| Lenalidomide | 5 | 8527 | Fludarabine | 9 | 1480 |
| Sunitinib | 4 | 6210 | Etoposide | 8 | 250 |
| Trastuzumab | 4 | 4276 | Carboplatin | 7 | 1650 |
| Alemtuzumab | 3 | 24506 | Doxorubicin liposomal | 7 | 6657 |
| GSK1120212 | 3 | NAb | Pemetrexed | 7 | 6995 |
| Others | 21 | NA | Others | 69 | NA |
NA = not applicable.
We calculated the four-week cost of anti-neoplastic agents for a standard patient (weight 70 kg, body surface area 1.73m2) using drug prices from the Red Book 2010 (24). Costs for physician visits, drug administration and supportive care were not included.
Investigational agent. Pricing is not available
In the last 30 days of life, the median number of anti-neoplastic agents administered was one (IQR 1-1) for targeted agents, one (IQR 1–2) for chemotherapeutic agents, and one (IQR 1–2) for any chemotherapy and targeted therapy among patients who received the respective treatments.
Factors Associated With Targeted and Chemotherapeutic Agent Use in the Last 30 Days of Life
Table 3 shows the separate univariate analysis for patient characteristics associated with targeted agent and chemotherapy use at the end of life. We found that young age, hematologic malignancies and lung cancer were associated with targeted therapy use in the last 30 days of life. Age and cancer type remained significant predictors of targeted therapy use in the multivariate analysis (Table 4).
Table 3.
Patient Characteristics by Targeted and Chemotherapeutic Agent Use in the Last 30 Days of Life (N=816)
| Targeted Therapy in the Last 30 Days of Life |
Chemotherapy in the Last 30 Days of Life |
|||||
|---|---|---|---|---|---|---|
| Patient Characteristics | No n=700 %a |
Yes n=116 %a |
P-valueb | No n=669 %a |
Yes n=147 %a |
P-value b |
| Age, yrs, mean (range) | 63 (22–97) |
60 (21–90) |
0.04 | 63 (22–97) |
60 (21–87) |
0.04 |
| Female sex | 339 (48) | 51 (44) | 0.37 | 316 (47) | 74 (50) | 0.50 |
| Race | ||||||
| White | 426 (61) | 73 (63) | 0.41 | 406 (61) | 93 (63) | 0.70 |
| Black | 158 (23) | 20 (17) | 148 (22) | 30 (20) | ||
| Hispanic | 81 (12) | 16 (14) | 83 (12) | 14 (10) | ||
| Asian | 28 (4) | 4 (3) | 24 (4) | 8 (5) | ||
| Others | 7 (1) | 3 (3) | 8 (1) | 2 (1) | ||
| Married | 434 (62) | 70 (60) | 0.71 | 418 (63) | 86 (59) | 0.35 |
| Education | 0.06 | 0.22 | ||||
| High school or less | 247 (48) | 37 (44) | 236 (48) | 48 (44) | ||
| College | 223 (43) | 33 (39) | 202 (41) | 54 (49) | ||
| Post-graduate | 48 (9) | 15 (18) | 55 (11) | 8 (7) | ||
| Cancer type | <0.001 | <0.001 | ||||
| Breast | 65 (9) | 6 (5) | 54 (8) | 17 (12) | ||
| Gastrointestinal | 159 (23) | 19 (16) | 152 (23) | 26 (18) | ||
| Genitourinary | 78 (11) | 11 (9) | 78 (12) | 11 (7) | ||
| Gynecologic | 60 (9) | 1 (1) | 49 (7) | 12 (8) | ||
| Head and neck | 44 (6) | 4 (3) | 45 (7) | 3 (2) | ||
| Hematologic | 75 (11) | 38 (33) | 64 (10) | 49 (33) | ||
| Other | 84 (12) | 10 (9) | 84 (13) | 10 (7) | ||
| Respiratory | 135 (19) | 27 (23) | 143 (21) | 19 (13) | ||
| Months between advanced cancer diagnosis and death, median (IQR) |
12 (4–25) | 13 (5–26) | 0.29 | 13 (5–26) | 8 (3–24) | 0.01 |
IQR = interquartile range.
Column percentage unless otherwise specified
We conducted two separate univariate analyses using the t-test for continuous, normally distributed variables (e.g., age), the Mann-Whitney test for continuous, non-parametric variables (e.g., duration between advanced cancer diagnosis and death), and Pearson's Chi-square test/Fisher's exact test for categorical variables (e.g., race).
Table 4.
Factors Associated With Targeted and Chemotherapeutic Agent Use in the Last 30 Days of Life in Multivariate Logistic Regression Analysis a
| Targeted Agents | Chemotherapy | |||||
|---|---|---|---|---|---|---|
| Odds Ratio |
95% CI | P-value | Odds Ratio |
95% CI | P-value | |
| Age (per year) | 0.98 | 0.97–1.00 | 0.013 | - | - | NSb |
| Cancer | <0.001 | <0.001 | ||||
| Breast | 1.0 | - | Ref | 1.0 | - | Ref |
| Gastrointestinal | 1.5 | 0.6–3.8 | 0.45 | 0.5 | 0.3–1.0 | 0.05 |
| Genitourinary | 1.8 | 0.6–5.2 | 0.28 | 0.4 | 0.2–1.0 | 0.05 |
| Gynecologic | 0.2 | 0.0–1.6 | 0.12 | 0.7 | 0.3–1.7 | 0.45 |
| Head and neck | 1.1 | 0.3–4.1 | 0.91 | 0.2 | 0.1–0.7 | 0.01 |
| Hematologic | 6.1 | 2.4–15.4 | <0.001 | 2.2 | 1.1–4.2 | 0.025 |
| Other | 1.3 | 0.5–3.9 | 0.59 | 0.3 | 0.1–0.7 | 0.008 |
| Respiratory | 2.6 | 1.0–6.6 | 0.05 | 0.3 | 0.2–0.7 | 0.004 |
| Survival <6 months between advanced cancer diagnosis and death |
- | - | NSb | 2.0 | 1.4–3.0 | <0.001 |
CI = confidence interval; NS = not significant.
Dependent variables included in the models were age, sex, race, marital status, cancer diagnosis, and survival <6 months between advanced cancer diagnosis and death to account for an aggressive disease course.
These variables were included in the multivariate logistic regression analysis but were removed from the models because of the lack of significance.
In the univariate analysis, patients who were young, had hematologic malignancies and a short interval between advanced cancer diagnosis and death were more likely to receive chemotherapy in the last 30 days of life (Table 3). Multivariate regression analysis showed that hematologic malignancies and a short duration between advanced cancer diagnosis and death were independently associated with chemotherapy administration (Table 4). In contrast, patients with head and neck, lung, genitourinary, gastrointestinal and other malignancies (e.g., central nervous system, sarcoma and thyroid) were less likely to receive chemotherapy at the end of life. Table 5 shows the median interval from last anti-cancer treatment to death by cancer type.
Table 5.
Median Duration Between Last Targeted and Chemotherapeutic Agent Use and Death
| Median Days Between Last Treatment and Death (95% CI) | |||
|---|---|---|---|
| Targeted Agents | Chemotherapeutic Agents |
Any Targeted or Chemotherapy Agents |
|
| Breast | 47(41–53) | 48 (39–57) | 47 (42–52) |
| Gastrointestinal | 55 (41–69) | 53 (44–62) | 51 (45–57) |
| Genitourinary | 74 (37–111) | 82 (39–125) | 74 (48–100) |
| Gynecologic | 61 (31–91) | 69 (36–102) | 67 (47–87) |
| Head and neck | 63 (29–97) | 119 (54–184) | 84 (3–165) |
| Hematologic | 26 (15–37) | 24 (15–33) | 26 (17–35) |
| Other | 59 (36–82) | 60 (46–74) | 61 (47–75) |
| Respiratory | 40 (22–58) | 86 (70–102) | 63 (43–83) |
| Overall | 47 (42–52) | 57 (51–63) | 53 (48–58) |
| P-valuea | 0.06 | <0.001 | <0.001 |
CI = confidence interval.
Log rank test comparing the duration among various tumor types.
Discussion
In this study, more than one in four patients received palliative systemic therapy within the last 30 days of life, and more than one in eight patients received targeted therapy during this period. Targeted agent use at the end of life was associated with younger age and hematologic and lung malignancies.
At our institution, targeted therapy was used almost as commonly as chemotherapy in the last 30 days of life, with a small proportion of patients receiving both. Our study had similar rates of patients receiving chemotherapy at the end of life relative to other studies using large population databases, although the interval between last chemotherapy and death was shorter in our cohort (median 57 days vs. >120 days) (6, 8, 12). This difference may be explained by the varying time periods, patient populations and settings. Furthermore, unlike population studies, we painstakingly reviewed the charts to exclude patients who died without evidence of disease.
The decision to start or to stop palliative systemic therapy is an intricate, technical and often emotionally charged judgment, particularly when the patient is near the end of life (13). It involves an educated estimation of the risks and benefits by the medical oncologist, guided by clinical evidence and various factors related to the disease, patients, physicians and practice patterns. As shown in this study, the type of malignancy determines the spectrum of available cancer treatment options, which, in turn, dictates treatment utilization. In addition, the cancer’s mutation profile allows oncologists to tailor therapy in the era of personalized medicine. Patient’s wishes, prognosis, comorbidities, performance status, adherence, and social support are often taken into consideration in the decision making process. Oncologists’ decisions also are potentially affected by their personal attitude, experience and training. Moreover, local practice patterns such as drug availability, health care policy and group culture may have an impact on whether a targeted agent is prescribed.
Targeted agents are often perceived to be more tolerable than chemotherapy. For instance, the National Cancer Institute stated that targeted therapy "may have fewer side effects than other types of cancer treatments”(14). Although nausea and vomiting, myelosuppression and alopecia generally occur less frequently than with chemotherapy, targeted agents are associated with many unique adverse effects, such as skin rashes, endocrine abnormalities, and electrolyte imbalances (15). Folliculitis occurs in up to 80% of patients on epidermal growth factor receptor inhibitors such as erlotinib and cetuximab, and can be associated with pain, pruritus and disfigurement (16, 17). Bevacizumab may infrequently cause life-threatening vascular catastrophes and impaired wound healing (18–20). Everolimus is associated with significant mucositis and electrolyte abnormalities (21). Sorafenib and sunitinib can both lead to severe fatigue, metabolic changes and hypothyroidism (22, 23).
In addition to the adverse effects and potential complications requiring hospitalization, there are many less obvious risks to consider when prescribing targeted therapy at the end of life, including frequent hospital visits, invasive investigations, and the tremendous financial burden associated with cancer treatments and supportive care (Table 2) (24). Furthermore, the pursuit of life-prolonging therapy could potentially delay transition of care, diverting patients’ precious time and energy to the pursuit of cancer treatments rather than planning ahead.
Palliative therapies are often prescribed with the intention of improving symptom control, sustaining hope and prolonging survival (25, 26). When a treatment is given in the last 30 days of life, the benefit is arguably negligible. However, it should be noted that clinicians often overestimate survival (27, 28); thus, the use of life expectancy as a criteria for quality of care may be challenging. Instead, performance status has been clearly shown to be an important prognostic and predictive factor (29). When a patient reaches an Eastern Cooperative Oncology Group performance status of 3 or more (or Karnofsky Performance Status of 40% or less), great caution should be exercised when prescribing palliative systemic therapies.
This is the first study to examine predictors of targeted therapy use at the end of life. We found that hematologic malignancy was associated with targeted therapy use. This is not surprising given that patients with hematologic malignancies generally have a poor quality of end-of-life care (8). Previous studies have shown that these patients are more likely to receive cytotoxic therapy at the end of life and to be admitted to and die in hospitals and intensive care units, and less likely to be referred to palliative and hospice care (10, 30–32). The availability of novel targeted agents for leukemia and lymphoma probably contributed to our observation. For the same reason, erlotinib is often available to lung cancer patients at the end of life. Our findings are consistent with a small cohort of 36 non-small cell lung cancer patients, in which 21 (58%) received erlotinib or gefitinib in the last three months of life (9). In contrast, patients with head and neck cancer, central nervous system tumors and sarcoma were less likely than patients with other tumor types to receive targeted therapy, likely because of the relative lack of standard targeted therapy options for these cancers. We also found that younger patients were more likely to receive targeted therapy at the end of life, consistent with other studies demonstrating that they are generally managed more aggressively than older patients (10).
This study has several limitations. First, findings in this study are solely based on patients who seek care at our comprehensive cancer center. Our institution offers a wide array of therapeutic options, including numerous clinical trials of novel agents and a large Phase I experimental therapy program. Many patients come specifically to seek further cancer treatments when no standard therapies exist. Because the patient characteristics, practice patterns and resource availability may differ from other oncology settings, further studies are needed to determine if our findings are generalizable. Second, in addition to the predictors identified above, several factors such as patient preference, performance status, comorbidities and clinician characteristics may determine whether patients receive anti-neoplastic therapy at the end of life. We were unable to include these variables because they were not routinely documented. Prospective studies could examine these factors in further detail. Third, we did not capture information on treatment toxicities because they were often mixed with patients’ underlying symptom burden. Fourth, we only included a short study period. Further studies are needed to examine the trends of targeted agent use at the end of life. Finally, by excluding patients who were not seen by our institution in the last three months of life, we could have inflated the proportion of patients who received chemotherapy/targeted agents at the end of life if these patients were less likely to seek aggressive treatments in the last three months. The opposite also may be true if many of these individuals decided to seek further treatments with their local oncologists after their last visit at our institution. Further studies are required to examine patients’ treatment patterns in the community.
In summary, targeted agents were used as often as chemotherapy at the end of life, particularly among younger patients and those with hematologic and lung malignancies. The use of chemotherapy in the last days of life has been established as a quality of end-of-life care indicator (7, 12). Our study raises the question whether targeted therapy also should be considered as another quality-of-care indicator. Given the increasing number of targeted therapeutic options and the growing number of clinical trials, we expect a sustained rise in the use of targeted agents at the end of life. Thus, we urgently need to develop guidelines on when to start and to stop palliative systemic therapies for cancer patients with a limited life expectancy.
Acknowledgments
Dr. Bruera is supported in part by National Institutes of Health grants RO1NR010162-01A1, RO1CA122292-01, and RO1CA124481-01. Dr. Hui is supported in part by an institutional start-up fund. This study also was supported by the M. D. Anderson Cancer Center Support Grant (CA 016672). The sponsors had no role in study design, data collection, analysis, interpretation, or writing of the report.
Footnotes
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Disclosures
The authors declare no conflicts of interest.
References
- 1.Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646–674. doi: 10.1016/j.cell.2011.02.013. [DOI] [PubMed] [Google Scholar]
- 2.de Bono JS, Ashworth A. Translating cancer research into targeted therapeutics. Nature. 2010;467:543–549. doi: 10.1038/nature09339. [DOI] [PubMed] [Google Scholar]
- 3.Saijo N. Progress in cancer chemotherapy with special stress on molecular-targeted therapy. Jpn J Clin Oncol. 2010;40:855–862. doi: 10.1093/jjco/hyq035. [DOI] [PubMed] [Google Scholar]
- 4.Hui D, Con A, Christie G, Hawley PH. Goals of care and end-of-life decision making for hospitalized patients at a canadian tertiary care cancer center. J Pain Symptom Manage. 2009;38:871–881. doi: 10.1016/j.jpainsymman.2009.05.017. [DOI] [PubMed] [Google Scholar]
- 5.Setoguchi S, Earle CC, Glynn R, et al. Comparison of prospective and retrospective indicators of the quality of end-of-life cancer care. J Clin Oncol. 2008;26:5671–5678. doi: 10.1200/JCO.2008.16.3956. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Earle CC, Landrum MB, Souza JM, et al. Aggressiveness of cancer care near the end of life: is it a quality-of-care issue? J Clin Oncol. 2008;26:3860–3866. doi: 10.1200/JCO.2007.15.8253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Earle CC, Park ER, Lai B, et al. Identifying potential indicators of the quality of end-of-life cancer care from administrative data. J Clin Oncol. 2003;21:1133–1138. doi: 10.1200/JCO.2003.03.059. [DOI] [PubMed] [Google Scholar]
- 8.Tang ST, Wu SC, Hung YN, et al. Determinants of aggressive end-of-life care for Taiwanese cancer decedents, 2001 to 2006. J Clin Oncol. 2009;27:4613–4618. doi: 10.1200/JCO.2008.20.5096. [DOI] [PubMed] [Google Scholar]
- 9.Wong AS, Teo C, Lim SW, et al. Targeted therapy at the end of life for patients with lung cancer. J Palliat Med. 2010;13:945–948. doi: 10.1089/jpm.2010.0084. [DOI] [PubMed] [Google Scholar]
- 10.Hui D, Elsayem A, Li Z, et al. Antineoplastic therapy use in patients with advanced cancer admitted to an acute palliative care unit at a comprehensive cancer center: a simultaneous care model. Cancer. 2010;116:2036–2043. doi: 10.1002/cncr.24942. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hui D, Kim SH, Kwon JH, et al. Access to palliative care before death among patients treated at a comprehensive cancer center. Oncologist. doi: 10.1634/theoncologist.2012-0192. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Earle CC, Neville BA, Landrum MB, et al. Trends in the aggressiveness of cancer care near the end of life. J Clin Oncol. 2004;22:315–321. doi: 10.1200/JCO.2004.08.136. [DOI] [PubMed] [Google Scholar]
- 13.Harrington SE, Smith TJ. The role of chemotherapy at the end of life:"When is enough, enough?". JAMA. 2008;299:2667–2678. doi: 10.1001/jama.299.22.2667. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.National Cancer Institute. Targeted therapy. [Accessed March 5, 2012];National Cancer Institute dictionary of cancer terms. 2012 Available from http://www.cancer.gov/dictionary?cdrid=270742.
- 15.Guevremont C, Alasker A, Karakiewicz PI. Management of sorafenib, sunitinib, and temsirolimus toxicity in metastatic renal cell carcinoma. Curr Opin Support Palliat Care. 2009;3:170–179. doi: 10.1097/SPC.0b013e32832e4681. [DOI] [PubMed] [Google Scholar]
- 16.Burtness B, Anadkat M, Basti S, et al. NCCN Task Force Report: Management of dermatologic and other toxicities associated with EGFR inhibition in patients with cancer. J Natl Compr Canc Netw. 2009;7(Suppl 1):S5–S21. doi: 10.6004/jnccn.2009.0074. quiz S22-24. [DOI] [PubMed] [Google Scholar]
- 17.Galimont-Collen AF, Vos LE, Lavrijsen AP, Ouwerkerk J, Gelderblom H. Classification and management of skin, hair, nail and mucosal side-effects of epidermal growth factor receptor (EGFR) inhibitors. Eur J Cancer. 2007;43:845–851. doi: 10.1016/j.ejca.2006.11.016. [DOI] [PubMed] [Google Scholar]
- 18.Daher IN, Yeh ET. Vascular complications of selected cancer therapies. Nat Clin Pract Cardiovasc Med. 2008;5:797–805. doi: 10.1038/ncpcardio1375. [DOI] [PubMed] [Google Scholar]
- 19.Gressett SM, Shah SR. Intricacies of bevacizumab-induced toxicities and their management. Ann Pharmacother. 2009;43:490–501. doi: 10.1345/aph.1L426. [DOI] [PubMed] [Google Scholar]
- 20.Zangari M, Fink LM, Elice F, et al. Thrombotic events in patients with cancer receiving antiangiogenesis agents. J Clin Oncol. 2009;27:4865–4873. doi: 10.1200/JCO.2009.22.3875. [DOI] [PubMed] [Google Scholar]
- 21.Soefje SA, Karnad A, Brenner AJ. Common toxicities of mammalian target of rapamycin inhibitors. Target Oncol. 2011;6:125–129. doi: 10.1007/s11523-011-0174-9. [DOI] [PubMed] [Google Scholar]
- 22.Torino F, Corsello SM, Longo R, Barnabei A, Gasparini G. Hypothyroidism related to tyrosine kinase inhibitors: an emerging toxic effect of targeted therapy. Nat Rev Clin Oncol. 2009;6:219–228. doi: 10.1038/nrclinonc.2009.4. [DOI] [PubMed] [Google Scholar]
- 23.Boers-Doets CB, Epstein JB, Raber-Durlacher JE, et al. Oral adverse events associated with tyrosine kinase and mammalian target of rapamycin inhibitors in renal cell carcinoma: a structured literature review. Oncologist. 2012;17:135–144. doi: 10.1634/theoncologist.2011-0111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Amir E, Seruga B, Martinez-Lopez J, et al. Oncogenic targets, magnitude of benefit, and market pricing of antineoplastic drugs. J Clin Oncol. 2011;29:2543–2549. doi: 10.1200/JCO.2011.35.2393. [DOI] [PubMed] [Google Scholar]
- 25.Grunfeld EA, Maher EJ, Browne S, et al. Advanced breast cancer patients' perceptions of decision making for palliative chemotherapy. J Clin Oncol. 2006;24:1090–1098. doi: 10.1200/JCO.2005.01.9208. [DOI] [PubMed] [Google Scholar]
- 26.Grunfeld EA, Ramirez AJ, Maher EJ, et al. Chemotherapy for advanced breast cancer: what influences oncologists' decision-making? Br J Cancer. 2001;84:1172–1178. doi: 10.1054/bjoc.2001.1733. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Christakis NA, Lamont EB. Extent and determinants of error in doctors' prognoses in terminally ill patients: prospective cohort study. BMJ. 2000;320:469–472. doi: 10.1136/bmj.320.7233.469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hui D, Kilgore K, Nguyen L, et al. The accuracy of probabilistic versus temporal clinician prediction of survival for patients with advanced cancer: a preliminary report. Oncologist. 2011;16:1642–1648. doi: 10.1634/theoncologist.2011-0173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Maltoni M, Caraceni A, Brunelli C, et al. Prognostic factors in advanced cancer patients: evidence-based clinical recommendations--a study by the Steering Committee of the European Association for Palliative Care. J Clin Oncol. 2005;23:6240–6248. doi: 10.1200/JCO.2005.06.866. [DOI] [PubMed] [Google Scholar]
- 30.Bruera E, Russell N, Sweeney C, Fisch M, Palmer JL. Place of death and its predictors for local patients registered at a comprehensive cancer center. J Clin Oncol. 2002;20:2127–2133. doi: 10.1200/JCO.2002.08.138. [DOI] [PubMed] [Google Scholar]
- 31.Hui D, Elsayem A, Palla S, et al. Discharge outcomes and survival of patients with advanced cancer admitted to an acute palliative care unit at a comprehensive cancer center. J Palliat Med. 2010;13:49–57. doi: 10.1089/jpm.2009.0166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Cheng WW, Willey J, Palmer JL, Zhang T, Bruera E. Interval between palliative care referral and death among patients treated at a comprehensive cancer center. J Palliat Med. 2005;8:1025–1032. doi: 10.1089/jpm.2005.8.1025. [DOI] [PubMed] [Google Scholar]