Originally published as JCO Early Release 10.1200/JCO.2005.03.9289 on March 27 2006

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Prospective Evaluation of the Relationship of Patient Age and Paclitaxel Clinical Pharmacology: Cancer and Leukemia Group B (CALGB 9762)

Stuart M. Lichtman, Donna Hollis, Antonius A. Miller, Gary L. Rosner, Chris A. Rhoades, Eric P. Lester, Frederick Millard, John Byrd, Stephen A. Cullinan, D. Marc Rosen, Robert A. Parise, Mark J. Ratain, Merrill J. Egorin

From the Cancer and Leukemia Group B; University of Chicago, Chicago; Illinois Oncology Research Assoc, Peoria, IL; North Shore University Hospital, New York University School of Medicine, Manhasset, NY; CALGB Statistical Center, Durham; Wake Forest University School of Medicine, Winston-Salem, NC; The Ohio State University Medical Center, Columbus, OH; University of California at San Diego, San Diego, CA; Walter Reed Army Medical Center, Washington, DC; University of Maryland Cancer Center, Baltimore, MD; University of Pittsburgh Cancer Institute and School of Medicine, Pittsburgh, PA.

Address reprint requests to Merrill J. Egorin, MD, University of Pittsburgh Cancer Institute, Hillman Cancer Center, 5117 Centre Ave, G.27e, Pittsburgh, PA 15213; e-mail: egorinmj{at}msx.upmc.edu

	ABSTRACT

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PURPOSE: To prospectively evaluate the pharmacokinetics and toxicity profile of paclitaxel in relation to patient age in adults 55 years old.

PATIENTS AND METHODS: Paclitaxel was administered at 175 mg/m² for 3 hours to 153 patients, 46 of whom were 75 years of age. Pharmacokinetic and toxicity assessments were performed. Data were analyzed by cohort (cohort 1, age 55 to 64 years; cohort 2, age 65 to 74 years; cohort 3, age 75 years).

RESULTS: Paclitaxel concentration versus time (AUC) and total-body clearance (CL_tb) data were available for 122 patients (cohort 1, 46 patients; cohort 2, 44 patients; cohort 3, 32 patients). Mean paclitaxel AUC increased across cohorts (P = .01). Mean (SE) AUCs were 22.4 (2.5) µmol/L x hour, 26.2 (2.8) µmol/L x hour, and 31.7 (5.6) µmol/L x hour for cohorts 1, 2, and 3, respectively. There was a corresponding significant (P = .007) age-related decrease in mean (SE) paclitaxel CL_tb (cohort 1, 11.0 [0.7] L/h/m²; cohort 2, 9.3 [0.6] L/h/m²; cohort 3, 8.2 [0.6] L/h/m²). Patients in cohort 3 experienced significantly lower absolute neutrophil count nadirs than did younger groups (P = .02). There was also a significant increase in percentage of patients with grade 3 neutropenia across age cohorts (cohort 1, 22%; cohort 2, 35%; cohort 3, 49%; P = .006). However, the increased exposure of patients to paclitaxel and increased neutropenia were not reflected in adverse clinical sequelae such as hospitalization for toxicity (P = .82), receiving intravenous antibiotics (P = .21), or experiencing a temperature more than 38°C (P = .45).

CONCLUSION: Although paclitaxel CL_tb decreases with increasing patient age, there is great interpatient variability. Cooperative group studies to evaluate the effect of aging on pharmacokinetics are feasible.

	INTRODUCTION

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The study of cancer and aging has emerged as an important issue in oncology. Persons older than 65 years are within the fastest growing segment of the US population and will account for an estimated 20% of Americans by the year 2030. Increasing age is directly associated with increasing rates of cancer, corresponding to an 11-fold greater incidence in persons older than 65 years as compared with persons younger than 65 years.¹ Despite the increasing incidence of cancer with aging and the aging of the population, elderly patients have been under-represented in clinical trials.^2,3 Consequently, oncologists making treatment decisions for older patients are hampered by the limited number of appropriate studies of single-agent and combination chemotherapy in elderly patients.^4,5

Many physiological changes that accompany human aging can affect drug disposition. These include increase in body fat, decrease in lean body mass, and decrease in total body water.^6-9 Renal function declines with age, and there is some evidence that age may also affect the activity of drug metabolizing enzymes.^10,11 Other age-related factors include comorbidity, functional decline, polypharmacy, and alterations in plasma protein concentrations.^12-14 These age-related changes highlight the need for clinical pharmacology studies in the elderly cancer population. Ideally, increased information about age-related changes in pharmacokinetic and pharmacodynamic behavior of chemotherapy drugs should enhance the efficacy and ameliorate the toxicities of such therapy.

Paclitaxel was evaluated in the current study because it is a commonly used, active antineoplastic agent that is included in a number of regimens used to treat elderly patients with a variety of malignancies.^15-19 In addition to using the standard, single-agent dose of paclitaxel, the study design incorporated a limited sampling strategy without a 24-hour, or later, specimen to optimize compliance and data collection in elderly cancer patients. The goal of this study was to determine the relationships of: (1) paclitaxel pharmacokinetics and age; (2) paclitaxel toxicity and age; and (3) paclitaxel pharmacokinetics and toxicity. The study was also intended to assess the feasibility of conducting pharmacokinetic studies of elderly patients in a multi-institutional setting.

	PATIENTS AND METHODS

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Eligibility
Patients were eligible if they were 55 years old, had an Eastern Cooperative Oncology Group (ECOG) performance score of 0, 1, or 2, and had histologic documentation of a measurable or assessable nonhematologic malignancy for which single-agent paclitaxel would be appropriate therapy. Patients were allowed one prior chemotherapy regimen, but prior paclitaxel therapy was prohibited. Patients had to be 4 weeks removed from prior radiation therapy or chemotherapy ( 6 weeks for nitrosoureas or mitomycin-C). Required laboratory data were granulocytes 1,500/µL, platelets 100,000/µL, and creatinine 1.5x the upper limit of normal, bilirubin 1.5 mg/dL, and AST 2.0x the upper limit of normal. Patients were assigned to cohorts based on age as follows: cohort 1, 55 to 64 years old; cohort 2, 65 to 74 years old; and cohort 3, 75 years old. Accrual to any cohort was temporarily suspended when that cohort had enrolled 20 patients and was not restarted until 20 patients had been enrolled in each cohort. The study was approved by the institutional review board of each participating institution, and before entry into the study, each patient signed an informed consent that had been approved by the institutional review board of the appropriate institution.

Pretreatment and Follow-Up Studies
A history and physical examination were done prestudy. A CBC, electrolytes, and chemistries were obtained prestudy and weekly during treatment.

Treatment
All patients received 175 mg/m² of paclitaxel intravenously (IV) over 3 hours on day 1 of a planned 21-day cycle of therapy. Before receiving paclitaxel, all patients received the following premedication: dexamethasone 20 mg by mouth 12 and 6 hours before paclitaxel infusion, diphenhydramine 50 mg IV 30 minutes before paclitaxel infusion, and cimetidine 300 mg intravenously or equivalent (ranitidine 50 mg or famotidine 20 mg) 30 minutes before paclitaxel infusion. Growth factors were not permitted.

Therapy, after cycle 1, including agents and doses administered, was at the discretion of each patient's treating physician. Patients continuing on single-agent paclitaxel underwent re-evaluation consisting of toxicity assessment, CBC, serum electrolytes, and renal and hepatic function tests.

Pharmacokinetics
The study utilized a sampling strategy that required 3 specimens.²⁰ Specifically, heparinized venous blood samples were drawn from a peripheral vein contralateral to the infusion site before treatment, and at 1 and 6 hours after start of the paclitaxel infusion. The actual times of sample acquisition were measured precisely and recorded. Blood samples were centrifuged at 4°C for 10 minutes at approximately 1,000 x g, and the resulting plasma was stored at –20°C, or colder, until analyzed.

Plasma paclitaxel concentrations were measured with a modification²¹ of the high-performance liquid chromatography method of Jamis-Dow et al.²² The area under the paclitaxel concentration versus time curve (AUC) was calculated from the equation²³:

AUC = 4.7 (concentration at 1 hour) + 10 (concentration at 6 hours) + 0.63 Total body clearance (CL_tb) was calculated from the relationship:

CL_tb = dose ÷ AUC. For each patient, CL_tb was calculated twice. The first calculation used the 175 mg/m² body-surface area-normalized dosage (L/h/m²). The second used the actual mg paclitaxel dose administered to that patient (L/h).

Statistical Methods
Sample size estimation, based on the estimated AUC derived from a limited-sampling algorithm,²⁰ considered the estimated variation of the true AUC in the population and uncertainty of this estimate. Forty patients per age cohort were determined sufficient to detect relatively small differences in AUC across cohorts, assuming a .05 significance level, 90% power, common within-group variances, and validity of previous population estimates. Specifically, there would be 90% power to detect a significant difference if the eldest group's AUC was 18 µmol/L x hour and the two other cohorts had AUCs of 15 µmol/L x hour.

A generalized Cochran-Mantel-Haenszel correlation statistic with rank score test²⁴ was used to compare the derived pharmacokinetic parameters and blood count nadirs across age groups. Percentages of patients with specific adverse events were compared across age groups using the Cochran-Armitage trend test.²⁵ Regression methods were applied to determine whether particular patient characteristics were related to pharmacokinetic values and pharmacodynamic end points. All quoted P values are two sided. In addition, the Spearman rank correlation coefficient²⁶ was used to evaluate the potential relationship of AUC to the following pharmacodynamic measures of toxicity: nadir absolute neutrophil count (ANC); fever; and the need for hospitalization or IV antibiotics.

Patient registration and data collection were managed by the Cancer and Leukemia Group B (CALGB) Statistical Center. Data quality was ensured by careful review of data by CALGB Statistical Center staff and by the study chairperson. Statistical analyses were performed by CALGB statisticians and were based on the study database that was frozen on May 27, 2003. As part of the quality assurance program of the CALGB, members of the CALGB Data Audit Committee visit all participating institutions at least once every 3 years to review source documents. The auditors verify compliance with federal regulations and protocol requirements, including those pertaining to eligibility, treatment, adverse events, tumor response, and outcome in a sample of protocols at each institution. Such on-site review of medical records was performed for a subgroup of 65 patients (42%) of the 155 patients treated under this study.

	RESULTS

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Patient Characteristics
One hundred fifty-three patients enrolled on this study between September 1997 and November 2002. Patient characteristics and diagnoses are listed in Tables 1 and 2, respectively. The oldest patient enrolled was 86 years old. There was a male predominance, and breast and lung cancers accounted for 49% (75 of 153) of the total study population.

View larger version (9K): [in this window] [in a new window]   Fig 1. Relationship of patient age and paclitaxel clearance calculated based on: (A) the 175-mg/m2 body surface area–normalized dose administered to all patients; or (B) the actual milligram dose administered to each patient. Points represent individual patients.

	DISCUSSION

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The current prospective study demonstrates that, in patients older than 54 years, aging is associated with changes in the pharmacokinetics of paclitaxel. Specifically, increasing age was associated with increased exposure to, and decreased CL_tb of, the drug administered as a 3-hour infusion. It is unclear whether these pharmacokinetic changes reflect physiological age-related changes, comorbid conditions, or increased use in elderly patients of concomitant medications such as statin lipid-lowering agents, which are known to inhibit CYP2C8.²⁹ However, this increased exposure was not associated with an increase in any of the adverse clinical outcomes measured (ie, fever, antibiotic use, or hospitalization). Unfortunately, there are several reasons that these results cannot definitively support the contention that older patients can be treated with a standard paclitaxel dose of 175 mg/m² and do not need dose reduction for their first cycle of therapy. First, the primary objective of the study was to assess potential age-related alterations in paclitaxel pharmacokinetics, and therefore, the cohort sizes were not calculated to define clinical outcomes with statistical significance. Second, while there were no documented age-related increases in adverse clinical outcomes, the progressive age-related decrease in percentage of patients with final ANCs raises concern about older patients dropping out of the study or being removed from the study for adverse events other than those monitored in the study. Furthermore, the increased dose modifications required in cohort 3, as opposed to cohorts 1 and 2, raises concerns as to the ability of older patients to tolerate the 175-mg/m² dose of paclitaxel.

Many aspects of the current study merit emphasis. The study design contributed to its successful completion and meeting of its accrual goals, particularly with the inclusion of 46 patients in the eldest cohort. The limited sampling strategy used reduced the inconvenience required of these elderly patients. Any large-scale prospective investigation, particularly one that hopes to accrue patients older than 75 years, must take into account the special needs of such patients. The current trial also had its limitations. Although when analyzed by cohort, increasing age was associated with decreased paclitaxel CL_tb, and the degree of variability within each cohort highlights the potential pitfalls associated with generalizations concerning aging and the elderly. Also, while the limited sampling strategy used was convenient and facilitated patient accrual, the decision not to obtain a 24-hour sample precluded assessment of the time that plasma paclitaxel concentrations exceeded 0.05 µmol/L, which is a pharmacokinetic parameter that has been correlated with paclitaxel-induced neutropenia.³⁰ Additionally, at the time the study was designed, the potential importance of unbound, as opposed to total, plasma paclitaxel concentrations³¹ was not fully appreciated, and the applicability of the limited sampling strategy to unbound paclitaxel concentrations was unknown. As a result, only total paclitaxel was measured in the current study; however, serum albumin did not correlate with paclitaxel CL_tb. Another limitation was that paclitaxel pharmacokinetics and pharmacodynamics were only evaluated in the first cycle of a potentially multicycle, every-3-week regimen. Therefore, no information was generated regarding changes in paclitaxel pharmacology, including cumulative toxicity, over multiple cycles. Furthermore, it is unclear how the observed age-related alterations in paclitaxel pharmacokinetics might be extrapolated to patients treated on weekly paclitaxel regimens and how the pharmacokinetic data generated in patients aged 55 years older might relate to patients younger than 45 years.^19,32,33 Finally, whereas single-agent paclitaxel is used, it is frequently combined with other agents. Therefore, age-related pharmacokinetic and pharmacodynamic changes in various combination regimens also need to be explored.

The current study represented an initial effort by a cooperative group to perform clinical pharmacology studies of antineoplastic agents in elderly patients. Obviously, studies of aging can be enhanced further by the inclusion of other aspects in trial design. Assessment of differences in clinical, rather than pharmacokinetic, aspects of drug treatment might be more useful primary objectives for future studies, though sample size considerations might render such objectives difficult to achieve. Consideration of deliverability of a regimen, rather than limiting evaluation to the initial cycle of therapy would also be desirable, but the logistics of follow-up of elderly patients through multiple cycles of treatment might prove problematic. Ideally, studies should include measures of geriatric functioning, such as basic and instrumental activities of daily living, as well as documentation of all concomitant medications. Studies in the vulnerable elderly or frail patients would also be extremely valuable as these groups comprise the majority of elderly cancer patients.³⁴ Studies in patients with excretory and drug-metabolizing end-organ dysfunction are also feasible and should be extended to include geriatric patients.^35-37 We believe that future studies will need to incorporate these various factors, and possibly others, to properly evaluate chemotherapy in older patients.

	Appendix

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The following institutions participated in this study:

CALGB Statistical Center, Durham, NC–Stephen George, PhD, supported by CA33601

Dana-Farber Cancer Institute, Boston, MA–George P. Canellos, MD, supported by CA32291

Duke University Medical Center, Durham, NC–Jeffrey Crawford, MD, supported by CA47577

Illinois Oncology Research Assoc, Peoria, IL–John W. Kugler, MD, supported by CA35113

Massachusetts General Hospital, Boston, MA–Michael L. Grossbard, MD, supported by CA12449

Mount Sinai School of Medicine, New York, NY–Lewis R. Silverman, MD, supported by CA04457

North Shore - Long Island Jewish Medical Center, Manhasset, NY–Daniel R. Budman, MD, supported by CA35279

Rhode Island Hospital, Providence, RI–William Sikov, MD, supported by CA08025

Roswell Park Cancer Institute, Buffalo, NY–Ellis Levine, MD, supported by CA02599

SUNY Upstate Medical University, Syracuse, NY–Stephen L. Graziano, MD, supported by CA21060

The Ohio State University Medical Center, Columbus, OH–Clara D. Bloomfield, MD, supported by CA77658

University of California at San Diego, San Diego, CA–Stephen L. Seagren, MD, supported by CA11789

University of California at San Francisco, San Francisco, CA–Alan P. Venook, MD, supported by CA60138

University of Chicago Medical Center, Chicago, IL–Gini Fleming, MD, supported by CA41287

University of Missouri/Ellis Fischel Cancer Center, Columbia, MO–Michael C. Perry, MD, supported by CA12046

University of Tennessee Memphis, Memphis, TN–Harvey B. Niell, MD, supported by CA47555

Wake Forest University School of Medicine, Winston-Salem, NC–David D. Hurd, MD, supported by CA03927

Walter Reed Army Medical Center, Washington, DC–Thomas Reid, MD, supported by CA26806

Washington University School of Medicine, St Louis, MO–Nancy Bartlett, MD, supported by CA77440

	Authors' Disclosures of Potential Conflicts of Interest

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Although all authors completed the disclosure declaration, the following authors or their immediate family members indicated a financial interest. No conflict exists for drugs or devices used in a study if they are not being evaluated as part of the investigation. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.

Authors Employment Leadership Consultant Stock Honoraria Research Funds Testimony Other Mark J. Ratain Bristol-Myers Squibb (A) Merrill J. Egorin Bristol-Myers Squibb (A) Bristol-Myers Squibb (A) Bristol-Myers Squibb (A)

Dollar Amount Codes (A) < $10,000 (B) $10,000-99,999 (C) $100,000 (N/R) Not Required

	Author Contributions

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Conception and design: Stuart M. Lichtman, Donna R. Hollis, Antonius A. Miller, Gary L. Rosner, Mark J. Ratain, Merrill J. Egorin Administrative support: Mark J. Ratain, Merrill J. Egorin Provision of study materials or patients: Stuart M. Lichtman, Antonius A. Miller, Chris A. Rhoades, Eric P. Lester, Frederick Millard, John C. Byrd, Stephen A. Cullinan Collection and assembly of data: Stuart M. Lichtman, D. Marc Rosen, Robert A. Parise, Merrill J. Egorin Data analysis and interpretation: Stuart M. Lichtman, Donna R. Hollis, Antonius A. Miller, Gary L. Rosner, D. Marc Rosen, Robert A. Parise, Mark J. Ratain, Merrill J. Egorin Manuscript writing: Stuart M. Lichtman, Donna R. Hollis, Antonius A. Miller, Gary L. Rosner, Mark J. Ratain, Merrill J. Egorin Final approval of manuscript: Stuart M. Lichtman, Donna R. Hollis, Antonius A. Miller, Gary L. Rosner, Chris A. Rhoades, Eric P. Lester, Frederick Millard, John C. Byrd, Stephen A. Cullinan, D. Marc Rosen, Robert A. Parise, Mark J. Ratain, Merrill J. Egorin

 

	ACKNOWLEDGMENTS

 
We thank Jeremy A. Hedges for outstanding secretarial support and the University of Pittsburgh Cancer Institute Hematology/Oncology Writing Group for constructive criticism in preparation of this manuscript.

	NOTES

 
Supported in part by grants from the National Cancer Institute (CA31946) to the Cancer and Leukemia Group B (Richard L. Schilsky, MD, Chairman).

Presented in part at the 37th Annual Meeting of the American Society of Clinical Oncology, San Francisco, CA, May 12-15, 2001, and the 94th Annual Meeting of the American Association of Cancer Research, Washington, DC, July 11-14, 2003.

The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted August 17, 2005; accepted December 20, 2005.

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