BRIEF COMMUNICATION

Criterion Validity of Medicare Chemotherapy Claims in Cancer and Leukemia Group B Breast and Lung Cancer Trial Participants

Elizabeth B. Lamont, James E. Herndon, II, Jane C. Weeks, I. Craig Henderson, Rogerio Lilenbaum, Richard L. Schilsky, Nicholas A. Christakis
for the Cancer and Leukemia Group B

Affiliations of authors: Department of Medicine and Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA (EBL); CALGB Statistical Center, Durham, NC (JEH); Department of Medicine, Dana-Farber Cancer Institute, Boston, MA (JCW); Department of Medicine, University of California, San Francisco, CA (ICH); Department of Medicine, Mount Sinai Cancer Center, Miami Beach, FL (RL); Department of Medicine, University of Chicago, Chicago, IL (RLS); Department of Health Care Policy, Harvard Medical School, Boston, MA (NAC)

Correspondence to: Elizabeth B. Lamont, MD, MS, Institute of Technology Assessment, Massachusetts General Hospital, 101 Merrimac Street, 10th Floor, Boston, MA 02114 (e-mail: elamont{at}partners.org).


    ABSTRACT
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To determine the accuracy with which Medicare claims data measure chemotherapy use in elderly Medicare beneficiaries with cancer, we performed a criterion validation study. We compared gold-standard clinical trial data for 175 elderly cancer patients treated in two Cancer and Leukemia Group B (CALGB) breast and lung cancer trials (i.e., 45 from trial 9344 and 130 from trial 9730) with contemporaneous ambulatory and in-patient Medicare health insurance claims data from Centers for Medicare and Medicaid Services (CMS). The breast trial participants studied were those elderly enrolled between 1995 and 1997 and treated with doxorubicin and cyclophosphamide or this combination with paclitaxel. The lung trial participants studied were those elderly enrolled between 1998 and 2000 and treated with paclitaxel and carboplatin or paclitaxel alone. Comparing CALGB data with Medicare claims, we found the crude sensitivity for chemotherapy administration was 93% (95% confidence interval [CI] = 88% to 96%). Individual chemotherapy agents had similarly high sensitivities, ranging from 81% (95% CI = 70% to 89%) for carboplatin to 91% (95% CI = 79% to 98%) for cyclophosphamide. Agent-specific specificities were 100%. CMS data reliably captured repeat administration of chemotherapy to within one cycle. Administrative Medicare claims data appear to be a valid source of information for chemotherapy administered to elderly Medicare beneficiaries with cancer.


The elderly are numerically underrepresented (13) and perhaps physiologically misrepresented (4) in clinical trials of anticancer therapy. Consequently, the expected benefits and toxicities of chemotherapy in the general population of elderly Americans may not be the same as those in trial participants. Nevertheless, clinicians need information about the expected benefits and toxicities of the chemotherapy in this group of patients. Because Medicare reimburses for intravenous administration of chemotherapy, Medicare claims are a potential source of observational data that could be used to understand the expected benefits and toxicities of chemotherapy. However, before Medicare claims regarding chemotherapy can be used to make robust causal inferences about the use and outcomes of chemotherapy in the elderly, very basic validation studies must first be completed (5). To determine the accuracy with which Medicare claims data capture chemotherapy use in elderly patients, we evaluated the criterion validity of Medicare chemotherapy claims by comparing an external, gold-standard measure of chemotherapy administration, Cancer and Leukemia Group B (CALGB) clinical trial data, with contemporaneous Medicare claims files from the Centers for Medicare and Medicaid Services (CMS).

We formed a retrospective cohort consisting of all patients ages 65 years or older enrolled in one of two CALGB trials: 52 patients from 9344, "Doxorubicin dose escalation, with or without Taxol, as part of the CA adjuvant regimen for node-positive breast cancer" (hereafter, "the CALGB breast cancer protocol") enrolled between 1995 and 1997 (6), and 186 patients from 9730, "Single-agent versus combination chemotherapy in advanced NSCLC (i.e., non–small-cell lung cancer), a CALGB randomized trial of efficacy, quality of life, and cost-effectiveness" (hereafter, "the CALGB lung cancer protocol") enrolled between 1998 and 2000 (7). We carefully linked the cohorts' CALGB clinical trial data (e.g., demographic information, information pertaining to chemotherapy administration) to their CMS Medicare claims files (i.e., denominator, Carrier, OUTPT, and MedPAR files) from the corresponding calendar period to create the CALGB-Medicare data set. We were able to match 228 (96%) of the 238 participants to Medicare files, a rate consistent with that in previous literature (8). Among these 228 eligible patients, 40 were removed from the analytic sample because of enrollment in health maintenance organizations whose claims were not processed through CMS and an additional 13 were removed because of a lack of enrollment in Medicare part B. The final analytic sample contained 175 patients (45 from CALGB 9344 and 130 from CALGB 9730).

Because all members of the analytic sample received chemotherapy, a crude, overall chemotherapy (i.e., non-agent-specific) specificity calculation that used patients as the unit of analysis was not possible. However, both CALGB trials restricted eligibility to patients who had received no prior chemotherapy for their lung or breast cancer and had no history of prior cancer. Therefore, we were able to use time period as the basis for calculating the crude sensitivity and specificity of the claims. We first defined two time periods for each patient, a pretrial time period, when chemotherapy was known not to have been given according to the gold standard, and an intratrial time period, when chemotherapy was known to have been given according to the gold standard. Claims present for care administered during the intratrial period provided information for the sensitivity, and claims present for care administered in the pretrial time provided information for the specificity.

A different approach was used to calculate agent-specific test characteristics. Because each patient was treated on only one nonoverlapping CALGB protocol,1 we estimated the agent-specific sensitivity and specificity with the patient as the unit of analysis by use of claims from the intratrial time period only. We evaluated results according to site of care (i.e., academic tertiary care medical center versus nonacademic tertiary care medical center) to inform generalizability. Finally, for patients on the paclitaxel arm of the CALGB lung cancer trial, we evaluated the accuracy with which Medicare claims files captured repeat administrations (i.e., cycles) of chemotherapy.

CALGB statisticians approved the statistical approaches used in analyzing these data. This study was approved by the University of Chicago and Massachusetts General Hospital institutional review boards and conducted in compliance with their regulations. All analyses were performed using STATA version 8 SE.

Table 1 describes the demographic and disease characteristics of the sample. After examining inpatient and ambulatory Medicare claims files (i.e., Carrier, OUTPT, and MedPAR files) for CALGB treatments rendered during the study period as described by the broad algorithm detailed in Table 2, we found that 163 (93%) of the 175 patients had at least one Medicare claim for chemotherapy during the intratrial period and only 13 (7%) of the 175 patients had any claim for chemotherapy during the pretrial period. The crude sensitivity was thus 93% (95% confidence interval [CI] = 88% to 96%), and the crude specificity was 93% (95% CI = 88% to 96%).


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Table 1.  Demographic and disease characteristics for the analytic sample containing 175 patients*

 

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Table 2.  Modified billing code taxonomy indicating chemotherapy administration*

 
Because this method of chemotherapy ascertainment includes both diagnostic and procedure codes that can refer to provider encounters for chemotherapy, as well as actual infusion of chemotherapy and the chemotherapy agents themselves, we investigated the test characteristics of a more precise ascertainment method, namely, the alphanumeric J9XXX codes for specific intravenous chemotherapy agents in the ambulatory Medicare files (i.e., Carrier and OUTPT files). Although 11 (6%) of the 175 patients appeared to receive at least some of the protocol chemotherapy treatment as inpatients, the sensitivity of the J9XXX codes in the ambulatory files was high at 89% (95% CI = 84% to 93%) and the specificity was high at 100% (i.e., there were no J9XXX codes in the ambulatory files in the pretrial period). That is, this more refined ascertainment algorithm eliminated all false-positive results. In reviewing the code patterns of the broad algorithm's false-positive results, we found that the ICD-9 (International Classification of Disease 9th Revision) diagnostic code V581 (i.e., "encounter or admission for chemotherapy") within ambulatory files accounted for all false-positive results in the remaining 13 patients. Adding the ICD-9 procedure code 99.25 to the J9XXXX algorithm, to identify those patients treated with chemotherapy exclusively as inpatients, and then screening both ambulatory and inpatient Medicare files lead to a further increase in sensitivity to 91% and did not diminish the specificity of 100%. Thus, in combination, the algorithm of procedure codes J9XXX applied to ambulatory files and ICD-9 procedure code 99.25 applied to the inpatient file yielded the highest combined sensitivity and specificity.

To determine agent-specific test characteristics, we investigated whether the following alphanumeric chemotherapy codes were present or absent in the ambulatory Medicare files (i.e., Carrier and OUTPT files) from the intratrial period for each patient: paclitaxel (HCPCS [Health Care Financing Adminstration Common Procedure Coding System] code J9265), carboplatin (HCPCS code J9045), doxorubicin (HCPCS codes J9000, J9001, J9010), and cyclophosphamide (HCPCS codes J9070, J9080, J9090-J9097). The 175 study participants included 11 patients who, according to Medicare files, appeared to have received at least some of their chemotherapy in an inpatient setting, a situation in which individual agents are not discernable. Among the 130 patients treated with paclitaxel according to CALGB, 112 (86%) had at least one J code in their ambulatory Medicare files, indicating the administration of paclitaxel (i.e., sensitivity = 86%, 95% CI = 79% to 92%). Among the 68 patients treated with carboplatin according to CALGB, 55 (81%) had at least one J code in their ambulatory Medicare files, indicating the administration of carboplatin (i.e., sensitivity = 81%, 95% CI = 70% to 98%). Among the 45 patients treated with doxorubicin according to CALGB, 41 (91%) had at least one J code in their ambulatory Medicare files, indicating the administration of doxorubicin (i.e., sensitivity = 91%, 95% CI = 79% to 98%). Among the 45 patients treated with cyclophosphamide according to CALGB, 41 had at least one J code in their ambulatory Medicare files, indicating the administration of cyclophosphamide (i.e., sensitivity = 91%, 95% CI = 79% to 98%). The corresponding specificities for each of these agents were 100%. Of note, these analyses may underestimate sensitivity because 11 (6%) of the 175 patients received at least some of their chemotherapy as inpatients, a situation in which individual agents are not discernable.

To evaluate the dependence of results on the type of treating institution (i.e., tertiary care academic medical centers versus nontertiary care academic medical centers), we replicated the analyses according to whether patients were enrolled in the studies at CALGB main member institutions or at CALGB community affiliates. We found that both crude sensitivity and specificity were nonstatistically significantly higher at community affiliate institutions than at main member institutions (i.e., sensitivity = 97% versus 90%, P = .07; specificity = 95% versus 89%, P = .20). For individual agents that were identifiable through ambulatory Medicare files with J codes, the results were of a similar magnitude and direction and were not uniformly statistically significant.

In our final analysis, we compared the number of distinct administrations of chemotherapy in the Medicare data with the number of cycles of treatment reported in the paclitaxel-only arm of the CALGB lung cancer cohort of 62 patients. We defined the total number of chemotherapy cycles administered as the sum of the number of temporally distinct occurrences of the paclitaxel code (J9265) in HCPCS fields in the ambulatory files plus inpatient chemotherapy infusion code 99.25 in ICD-9 procedure fields in the inpatient file during the study period. For 89% of lung cancer patients treated on the paclitaxel-only arm, CMS data measured the correct number of cycles of chemotherapy to within one cycle (61.3% patients had the same number of cycles in both data sources, 27.4% had one fewer cycle in CMS data than in CALGB data, 4.8% had two fewer cycles in CMS data than in CALGB data, 4.8% had three fewer cycles in CMS data than in CALGB data, and 1.6% had six fewer cycles in CMS data than in CALGB data).

This criterion validation study of Medicare chemotherapy claims shows that, for elderly Medicare beneficiaries with lung and breast cancer who were treated in one of two randomized, phase III CALGB trials, contemporaneous Medicare claims files reflect the clinical trial therapies with a high degree of drug-specific and overall sensitivity and specificity. We show that determining chemotherapy administration through reliance on only the J9XXX codes, indicating individual drugs administered intravenously, is associated with similarly high sensitivity but with greater specificity in our sample. The values of these test characteristics varied little by drug or by site of care, hinting at a generalizability to other chemotherapy drugs and to nonacademic medical centers. The study also shows that repeated administrations of chemotherapy (i.e., in cycles) are reliably captured to within one cycle for 89% of patients. Broadly, these results support the validity of the growing body of published observational research that uses Medicare chemotherapy claims from within the National Cancer Institute's SEER-Medicare data (920) to describe chemotherapy use and outcomes among elderly Medicare beneficiaries.


    NOTES
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1 Of note, paclitaxel was included in both the breast and lung cancer trials. However, during the study years, Medicare only reimbursed standard therapies administered clinical trials, not experimental treatments. Given that the paclitaxel was an experimental therapy at the time of the breast cancer trial, Medicare claims would not be expected to capture its use. Back

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.

The following institutions participated in one or both studies, CALGB 9344 and CALGB 9730: Baptist Cancer Institute CCOP, Memphis, TN—Lee S. Schwartzberg, MD (supported by CA71323); CALGB Statistical Office, Durham, NC—Stephen George, PhD (supported by CA33601); Christiana Care Health Services, Inc., CCOP, Wilmington, DE—Stephen Grubbs, MD (supported by CA45418); Community Hospital–Syracuse CCOP, Syracuse, NY—Jeffrey Kirshner, MD (supported by CA45389); Dana Farber Cancer Institute, Boston, MA—George P. Canellos, MD (supported by CA32291); Dartmouth Medical School–Norris Cotton Cancer Center, Lebanon, NH—Marc S. Ernstoff, MD (supported by CA04326); Duke University Medical Center, Durham, NC—Jeffrey Crawford, MD (supported by CA47577); Eastern Cooperative Oncology Group, Philadelphia, PA—Robert L. Comis, MD, Chairman (supported by CA23318); Georgetown University Medical Center, Washington, DC—Edward Gelmann, MD (supported by CA77597); Green Mountain Oncology Group CCOP, Bennington, VT—H. Herbert Mauer, MD (supported by CA35091); Illinois Oncology Research CCOP, Peoria, IL—John W. Kugler, MD (supported by CA35113); Impath Predictive Oncology, New York, NY—Placido P. Ferreira. MD; Kaiser Permanente CCOP, San Diego, CA—Jonathan A. Polikoff, MD (supported by CA45374); Long Island Jewish Medical Center, Lake Success, NY—Marc Citron, MD (supported by CA11028); Massachusetts General Hospital, Boston, MA—Michael L. Grossbard, MD (supported by CA12449); Medical University of South Carolina, Charleston, SC—Mark Green, MD, (supported by CA03927); Missouri Baptist Medical Center, St. Louis, MO–Alan P. Lyss, MD (supported by CA31946); Mount Sinai Medical Center CCOP—Miami, Miami Beach, FL—Rogerio Lilenbaum, MD (supported by CA45564); Mount Sinai School of Medicine, New York, NY—Lewis Silverman, MD (supported by CA04457); North Central Cancer Treatment Group, Rochester, MN—Michael J O'Connell, MD, Chairman (supported by CA25224); North Shore University Hospital, 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); South New Jersey CCOP, Camden, NJ—Jack Goldberg, MD (supported by CA54697); Southeast Cancer Control Consortium Inc. CCOP, Goldsboro, NC—James N. Atkins, MD (supported by CA45808); Southern Nevada Cancer Research Foundation CCOP, Las Vegas, NV—John Ellerton, MD (supported by CA35421); Southwest Oncology Group, San Antonio, TX—Charles Coltman, Jr., MD, Chairman (supported by CA32102); St. Michael's Medical Center Tri-County CCOP, Paterson, NJ—Arnold D. Rubin, MD (supported by CA60247); SUNY Upstate Medical University, Syracuse, NY—Stephen L. Graziano, MD (supported by CA21060); Syracuse Hematology-Oncology Association CCOP, Syracuse, NY—Jeffrey Kirshner, MD (supported by CA45389); The Ohio State University Medical Center, Columbus, OH—Clara D Bloomfield, MD (supported by CA77658); University of Alabama Birmingham, Birmingham, AL—Robert Diasio, MD (supported by CA47545); 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 Illinois at Chicago, Chicago, IL—Lawrence Feldman, MD (supported by CA74811); University of Iowa Hospitals, Iowa City, IA—Gerald H. Clamon, MD (supported by CA47642); University of Maryland Cancer Center, Baltimore, MD—Martin Edelman, MD (supported by CA31983); University of Massachusetts Medical Center, Worcester, MA—F. Mary Ellen Taplin, MD; (supported by CA37135); University of Minnesota, Minneapolis, MN—Bruce A. Peterson, MD (supported by CA16450); University of Missouri/Ellis Fischel Cancer Center, Columbia, MO—Michael C. Perry, MD (supported by CA12046); University of Nebraska Medical Center, Omaha, NE—Anne Kessinger, MD (supported by CA77298); University of North Carolina at Chapel Hill, Chapel Hill, NC—Thomas C. Shea, MD (supported by CA47559); University of Tennessee Memphis, Memphis, TN—Harvey B. Niell, MD (supported by CA47555); VA Western New York Healthcare System, Buffalo, NY—Lynn M. Steinbrenner, MD (supported by CA02599); Vermont Cancer Center, Burlington, VT—Hyman B. Muss, MD (supported by CA77406); Virginia Commonwealth University MB CCOP, Richmond, VA—John D. Roberts, MD (supported by CA52784); Wake Forest University School of Medicine, Winston-Salem, NC—David D. Hurd, MD (supported by CA03927); Walter Reed Army Medical Center, Washington, DC—Joseph J. Drabeck, MD (supported by CA26806); Washington University School of Medicine, St. Louis, MO—Nancy Bartlett, MD (supported by CA77440); and Weill Medical College of Cornell University, New York, NY—Scott Wadler, MD (supported by CA07968).

The study was supported, in part, by grants from the National Cancer Institute (CA93892 to Elizabeth Lamont, MD), the American Cancer Society (institutional grant to the University of Chicago Cancer Center), and the Department of Medicine, University of Chicago. The research for CALGB 9344 and 9730 was supported, in part, by grants from the National Cancer Institute: CA31946 to the CALGB—Richard L. Schilsky, MD, Chairman; CA33601 to the CALGB Statistical Center, Durham, NC—Stephen George, PhD; CA32291 to Dana Farber Cancer Institute—George P. Canellos; CA47577 to Duke University Medical Center, Durham, NC—Jeffrey Crawford, MD; CA60138 to the University of California at San Francisco, San Francisco, CA—Alan P. Venook, MD; CA45564 to Mount Sinai Medical Center, Miami, FL—Rogerio Lilenbaum, MD; and CA41287 to University of Chicago Medical Center, Chicago, IL—Gini Fleming, MD.

We are grateful to Jeannette Dowell of the CALGB Statistical Center for assembly and preparation of the CALGB data and Laurie Meneades of the Department of Health Care Policy at Harvard Medical School for preparation of the CMS data. We also appreciate statistical advice from Dr. Elk Halpern, PhD, of the Institute of Technology Assessment of Massachusetts General Hospital. We also thank participants of the Dana Farber/Harvard Cancer Center Cancer Outcome Research Program Seminar for helpful suggestions. Finally, we appreciate methodologic advice from Drs. Diane Lauderdale, Will Manning, and Ron Thisted of the Department of Health Studies at the University of Chicago.


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Manuscript received February 12, 2005; revised May 5, 2005; accepted May 9, 2005.



             
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