Delivering adjuvant chemotherapy to women with early-stage breast carcinoma
2001; Wiley; Volume: 92; Issue: 6 Linguagem: Inglês
10.1002/1097-0142(20010915)92
ISSN1097-0142
AutoresBrian K. Link, G. Thomas Budd, Shannon D. Scott, Elliot Dickman, D Paul, Grant Lawless, Martin Lee, Moshe Fridman, Jon M. Ford, William B. Carter,
Tópico(s)HER2/EGFR in Cancer Research
ResumoCancerVolume 92, Issue 6 p. 1354-1367 Original ArticleFree Access Delivering adjuvant chemotherapy to women with early-stage breast carcinoma Current patterns of care† Brian K. Link M.D., Corresponding Author Brian K. Link M.D. brian-link@uiowa.edu Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa Fax: (319) 353-8383University of Iowa Hospitals and Clinics, C32-GH, Iowa City, IA 52242===Search for more papers by this authorG. Thomas Budd M.D., G. Thomas Budd M.D. Cleveland Clinic Foundation, Cancer Center, Cleveland, OhioSearch for more papers by this authorShane Scott Pharm.D., Shane Scott Pharm.D. College of Pharmacy and Holden Comprehensive Cancer Center, The University of Iowa, Iowa City, IowaSearch for more papers by this authorElliot Dickman M.D., Ph.D., Elliot Dickman M.D., Ph.D. Hematology-Oncology, Meridia Cancer Institute, Mayfield Heights, OhioSearch for more papers by this authorDavid Paul M.D., David Paul M.D. Internists, Oncologists, LTD., Phoenix, ArizonaSearch for more papers by this authorGrant Lawless M.D., R.Ph., Grant Lawless M.D., R.Ph. Highmark Blue Cross/Blue Shield, Pittsburgh, Pennsylvania Pharmacoeconomics, Amgen, Inc., Thousand Oaks, CaliforniaSearch for more papers by this authorMartin W. Lee M.D., Martin W. Lee M.D. Park Nicollet Institute, St. Louis Park, MinnnesotaSearch for more papers by this authorMoshe Fridman Ph.D., Moshe Fridman Ph.D. AMF Consulting, Inc., Los Angeles, California Moshe Fridman is a statistical consultant who was supported by a grant from Amgen, Inc.Search for more papers by this authorJon Ford Ph.D., Jon Ford Ph.D. Health Economics, Amgen, Inc., Thousand Oaks, CaliforniaSearch for more papers by this authorWilliam B. Carter Ph.D., William B. Carter Ph.D. Pharmacoeconomics, Amgen, Inc., Thousand Oaks, CaliforniaSearch for more papers by this authorOncology Practice Pattern Study Working Group , Oncology Practice Pattern Study Working Group The Oncology Practice Pattern Study Working Group members are: G. T. Budd, M.D., and M. Markman, M.D. (Cleveland Clinic Foundation, Cleveland, OH); V. Caggiano, M.D. (Sutter Health, Eastern Division, Sacramento, CA); E. Chrischilles, Ph.D., B. Link, M.D., and S. Scott, Pharm.D. (University of Iowa, Iowa City, IA); E. Dickman, M.D., Ph.D. (Meridia Cancer Institute, Mayfield Heights, OH); G. Holmquist, R.Ph. (Group Health Cooperative, Seattle, WA); R. Jacobs, M.D. (LeGrange Oncology Associates, LeGrange, IL); R. Kerr, M.D., and W. Thames, Jr., R.Ph. (Southwest Regional Cancer Center, Austin, TX); G. Lawless, M.D., R.Ph. (Highmark Blue Cross/Blue Shield, Pittsburgh, PA); M. W. Lee, M.D. (Park Nicollet Institute, St. Louis Park, MN); A. Lopez, M.D., and B. Fireman, M.S. (The Permanente Medical Group, Inc., San Francisco, CA); D. Paul, M.D.(Internists, Oncologists, LTD., Phoenix, AZ); R. Rosenbluth, M.D. (APN, Fort Lee, NJ); J. Weeks, M.D., M.Sc. (Dana-Farber Cancer Institute, Boston, MA); W. Carter, Ph.D., J. Ford, Ph.D., and D. Delgado, Ph.D. (Amgen, Inc., Thousand Oaks, CA); M. Fridman, Ph.D. (AMF Consulting, Inc., Los Angeles, CA); and G. Smits, Ph.D. (CFC, Inc., Olivenhain, CA).Search for more papers by this author Brian K. Link M.D., Corresponding Author Brian K. Link M.D. brian-link@uiowa.edu Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa Fax: (319) 353-8383University of Iowa Hospitals and Clinics, C32-GH, Iowa City, IA 52242===Search for more papers by this authorG. Thomas Budd M.D., G. Thomas Budd M.D. Cleveland Clinic Foundation, Cancer Center, Cleveland, OhioSearch for more papers by this authorShane Scott Pharm.D., Shane Scott Pharm.D. College of Pharmacy and Holden Comprehensive Cancer Center, The University of Iowa, Iowa City, IowaSearch for more papers by this authorElliot Dickman M.D., Ph.D., Elliot Dickman M.D., Ph.D. Hematology-Oncology, Meridia Cancer Institute, Mayfield Heights, OhioSearch for more papers by this authorDavid Paul M.D., David Paul M.D. Internists, Oncologists, LTD., Phoenix, ArizonaSearch for more papers by this authorGrant Lawless M.D., R.Ph., Grant Lawless M.D., R.Ph. Highmark Blue Cross/Blue Shield, Pittsburgh, Pennsylvania Pharmacoeconomics, Amgen, Inc., Thousand Oaks, CaliforniaSearch for more papers by this authorMartin W. Lee M.D., Martin W. Lee M.D. Park Nicollet Institute, St. Louis Park, MinnnesotaSearch for more papers by this authorMoshe Fridman Ph.D., Moshe Fridman Ph.D. AMF Consulting, Inc., Los Angeles, California Moshe Fridman is a statistical consultant who was supported by a grant from Amgen, Inc.Search for more papers by this authorJon Ford Ph.D., Jon Ford Ph.D. Health Economics, Amgen, Inc., Thousand Oaks, CaliforniaSearch for more papers by this authorWilliam B. Carter Ph.D., William B. Carter Ph.D. Pharmacoeconomics, Amgen, Inc., Thousand Oaks, CaliforniaSearch for more papers by this authorOncology Practice Pattern Study Working Group , Oncology Practice Pattern Study Working Group The Oncology Practice Pattern Study Working Group members are: G. T. Budd, M.D., and M. Markman, M.D. (Cleveland Clinic Foundation, Cleveland, OH); V. Caggiano, M.D. (Sutter Health, Eastern Division, Sacramento, CA); E. Chrischilles, Ph.D., B. Link, M.D., and S. Scott, Pharm.D. (University of Iowa, Iowa City, IA); E. Dickman, M.D., Ph.D. (Meridia Cancer Institute, Mayfield Heights, OH); G. Holmquist, R.Ph. (Group Health Cooperative, Seattle, WA); R. Jacobs, M.D. (LeGrange Oncology Associates, LeGrange, IL); R. Kerr, M.D., and W. Thames, Jr., R.Ph. (Southwest Regional Cancer Center, Austin, TX); G. Lawless, M.D., R.Ph. (Highmark Blue Cross/Blue Shield, Pittsburgh, PA); M. W. Lee, M.D. (Park Nicollet Institute, St. Louis Park, MN); A. Lopez, M.D., and B. Fireman, M.S. (The Permanente Medical Group, Inc., San Francisco, CA); D. Paul, M.D.(Internists, Oncologists, LTD., Phoenix, AZ); R. Rosenbluth, M.D. (APN, Fort Lee, NJ); J. Weeks, M.D., M.Sc. (Dana-Farber Cancer Institute, Boston, MA); W. Carter, Ph.D., J. Ford, Ph.D., and D. Delgado, Ph.D. (Amgen, Inc., Thousand Oaks, CA); M. Fridman, Ph.D. (AMF Consulting, Inc., Los Angeles, CA); and G. Smits, Ph.D. (CFC, Inc., Olivenhain, CA).Search for more papers by this author First published: 27 September 2001 https://doi.org/10.1002/1097-0142(20010915)92:6 3.0.CO;2-PCitations: 60 † Neupogen® (G-CSF) is produced and sold by Amgen, Inc., where Grant Lawless, Jon Ford, and William B. Carter are employees. AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract BACKGROUND Variations in practice patterns are markers for the quality of patient care in general medicine, but little is known about variation in care delivered to cancer patients. This study's purpose was to describe chemotherapy use, variations in chemotherapy delivery, and the incidence of complications in community practice settings. METHODS Data describing adjuvant chemotherapy for patients with early-stage breast carcinoma (ESBC) were collected from an ongoing Oncology Practice Pattern Study at 13 large managed care, academic, and community practices (1111 patients). Data collection included information about diagnoses and adjuvant chemotherapy treatments, laboratory results, supportive care, complications, and treatment modifications. RESULTS The median patient age was 50 years, and most patients had zero to three positive lymph nodes. Chemotherapy regimens consisting of cyclophosphamide, methotrexate, and 5-fluororacil (CMF) and of doxorubicin and cyclophosphamide (AC) accounted for 76% of the adjuvant therapies used. Overall, 30% of patients had delivered average relative dose intensities ≤ 85% of the referenced targets. Delivered summation dose intensities (SDIs) frequently were well below targeted SDIs. Neutropenia-related dose modifications occurred for 27.6% of patients and recurred with a 60.7% rate. AC was the regimen delivered with a dose intensity closest to the referenced target. However, patients who were treated with AC regimens and with regimens consisting of cyclophosphamide, doxorubicin, and 5-fluorouracil had significantly higher rates of chemotherapy-related complications compared with patients who were treated with CMF regimens in the most recent treatment years. CONCLUSIONS Adjuvant chemotherapy for patients with ESBC frequently is not administered as referenced in off-protocol community settings. Variation in the delivered SDI raises concerns about potential treatment outcomes and warrants strategies to identify patients who are at risk for complications early in therapy. Cancer 2001;92:1354–67. © 2001 American Cancer Society. It has been well documented that variations in practice patterns are associated with patient outcome and serve as markers for quality of patient care in general medical practice.1 Little is known about the variations in the delivery of care to cancer patients despite the well-recognized impact of treatment on outcome in patients with certain malignancies. Breast carcinoma is the most common malignancy and the second leading cause of cancer deaths in women in the United States.2 Early detection and definitive surgical management are the foundation of curative strategies. Adjuvant treatment with chemotherapy or hormonal therapy has been shown in carefully controlled clinical trials to improve incrementally recurrence free and overall survival rates after achieving surgical control of the primary tumor. Clinicians traditionally have had several different combinations of anthracyclines, cyclophosphamide, methotrexate, and 5-fluorouricil available3-11 without clear guidance regarding the most effective regimen. The role of anthracyclines and the importance of dose intensity (DI) remain controversial. The importance of DI in optimal strategies for adjuvant chemotherapy remains under intense study. Evidence from several randomized clinical trials support the hypothesis that diminished intensity of chemotherapy in some regimens may adversely affect the expected benefit, however, the shape of any dose-response curve is not known.12-18 Bonadonna et al.12 explored the importance of delivered dose and introduced the concept that the amount of chemotherapy given may be related to patient outcome12: Women who received at least 85% of the planned dose of CMF had better recurrence free and overall survival rates after 20 years of follow-up compared with women who received less chemotherapy. Furthermore, the recurrence free survival rate for women who received less than 85% of the planned dose did not differ statistically from the untreated controls. Hryniuk et al.15 hypothesized that delivered DI, a measure of dose given per unit of time, was associated with improved outcomes in trials of adjuvant chemotherapy for patients with Stage II breast carcinoma.13-15 Results from Cancer and Leukemia Group B (CALGB) Study 8541 demonstrated that women who received a lower dose and dose-intense version of a cyclophosphamide, doxorubicin, and 5-fluororacil (CAF) regimen experienced a significantly higher rate of recurrence and reduced overall survival;16-18 however, randomized studies do not routinely indicate an improvement in outcome from modest dose escalations of either doxorubicin16, 17, 19 or cyclophosphamide.16, 17, 20-22 Although the reported relative advances in recurrence free and overall survival with adjuvant chemotherapy are often modest, when applied to a large number of women, the absolute number of lives saved may be substantial. Although many clinical trials of adjuvant therapy are performed in academic settings, the delivery of this therapy is considered standard practice for appropriately trained physicians in community practice, allowing for realization of the theoretic absolute benefits. When chemotherapy regimens are used in large community settings, the heterogeneous population of patients and practice environments allow for more significant variations in delivery than are represented in controlled trial settings. Factors such as patient age, comorbidities, and disease characteristics may have an impact on the choice of treatment regimens, and chemotherapy toxicities (mucositis, neutropenia, etc.) or patient preferences may have an impact on the intensity with which chemotherapy is delivered. In clinical (nonresearch protocol) practice, these potential variations in the treatment of patients with early-stage breast carcinoma are largely undocumented. For example, the choice of chemotherapy regimens, frequency of anthracycline use, intensity with which chemotherapy is delivered, and factors related to the above in community practice are unknown. The purpose of this study is to describe recent practices in the use of chemotherapy, variations in the planned and delivered doses of chemotherapy, and the incidence of chemotherapy-induced complications. Herein, we present findings from an oncology practice pattern study at large managed care, community, and academic practices across the United States. MATERIALS AND METHODS Study Design and Data Collection Data are reported from 13 of 15 diverse practice settings across the United States that have completed this ongoing historic case series study. Study sites include three managed care organizations, two academic cancer centers, two integrated hospital systems, and five community practices. The first study site was enrolled in 1996, with data collection completed by the end of 2000. The procedures followed in this protocol were approved by each site's Institutional Review Board. At 11 of 13 sites, data collection started from the date of Institutional Review Board approval and proceeded backward in time until approximately 100 consecutive eligible patient records were reviewed. At two sites, random samples of 100 patients were drawn from all eligible patients who were treated between 1993 and 1996, identified from a state wide SEER data base. Study patients were eligible if they received adjuvant chemotherapy for early-stage (i.e., Stage I, II, or III) breast carcinoma within 3 years of study initiation and were age ≥ 18 years. Patients were excluded if they were on a clinical research protocol, had other primary invasive malignancies, received a previous course of chemotherapy within 3 years of the course studied, or were positive for human immunodeficiency virus. Patients who received high-dose chemotherapy requiring stem cell rescue were excluded from eligibility. The medical records were abstracted using a standardized clinical report form (CRF) under the supervision of the site principal investigator. Information collected included 1) patient characteristics, including age, ethnicity, comorbidity, height, weight for each cycle, body surface area (BSA), tumor stage (defined according to the TNM staging criteria), and number of positive lymph nodes; 2) the planned chemotherapy regimen, including the drugs, dose, route of administration, and number and length of cycles; 3) the delivered chemotherapy regimen, including drugs, dose, route of administration, and the dates delivered for each cycle; 4) all complete blood counts and differential information available; 5) growth factor and antibiotic use during the course of therapy, including drugs, dose, number of doses, and dates delivered; 6) prior and concurrent radiation therapy, including courses, total doses, and dates delivered; 7) characteristics of the primary surgical treatment; 8) short-term treatment complications, including the presence of mucositis, febrile neutropenia (FN), and hospitalizations along with event dates, supporting documentation (pertinent notes from the medical record), and laboratory results; and 9) any medical record notation regarding chemotherapy dose modifications, complications, use of supportive care, and early termination of chemotherapy. Study Sample A total of 1265 medical records of eligible patients were abstracted from the 13 study sites reported here, with a range of 63–127 records per site. Thirty-one records (2.5%) were excluded because key information was missing (e.g., chemotherapy dose and schedule information, BSA), and 123 patients (9.7%) who received radiotherapy concurrent with chemotherapy were excluded. A total of 1111 patient records (88%) were available for analysis. Data Processing A single data coordinating center (DCC) located at Amgen (Thousand Oaks, CA) conducted study quality assurance, data entry, and data analyses. DCC staff included data entry staff, SAS programmers, and a multidisciplinary team of scientists, including clinicians (oncologists, pharmacists, and oncology nurses), biostatisticians, an epidemiologist, a health economist, and a health services researcher. Quality assurance and data analysis were coordinated and reviewed with the principal investigators and data collection coordinators at each site. An experienced oncology nurse reviewed all CRFs for completeness and consistencies. Questions were returned to the study site for verification against the medical record. After CRFs were reviewed and corrected, data were double entered to minimize data entry errors. Quality assurance was performed in the initial data analyses, examining variables for appropriate ranges of values and for consistency across related fields. Method for Calculating the Charlson Comorbidity Index Having a method to control for case mix is important for understanding variations in both treatment choices and patient outcomes. The Charlson Comorbidity Index (Charlson score) is a widely used comorbitity index with known reliability and validity.23-25 It was developed from analyses of the correlations between comorbid conditions and mortality in a patient cohort from an internal medicine inpatient service and was validated in a cohort of patients with breast carcinoma who had a 10-year follow-up for mortality. A total of 19 conditions with a relative risk of death at 1 year of 1.2 or greater were retained in the index. The relative risk of death was used to assign a weight to each condition (i.e., a condition with a relative risk between ≥ 1.2 and 1.5 was assigned a weight of 1; a relative risk between ≥ 1.5 and < 2.5 was assigned a weight of 2; a relative risk between ≥ 2.5 and < 3.5 was assigned a weight of 3; and the relative risk for two conditions, a second metastatic tumor and autoimmunodeficiency syndrome, was assigned a weight of 6). The score for an individual was calculated by summing the weights of each of the 19 comorbid conditions present. The sum may be presented as a simple score or grouped into four ordinal categories: 0, 1–2, 2–4, and ≥ 5. The Charlson score was calculated for each study patient by comparing the ICD 9 codes recorded from medical record review with the ICD 9 codes for the 19 comorbid conditions included in the Charlson score and summing the corresponding weights for each match. Scores are reported in ordinal categories. Classification of Chemotherapy Regimens Each patient was assigned a regimen code based on the planned chemotherapy regimens that were either abstracted directly from the medical record or inferred from the Cycle 1 prescriptions. Together with dose, schedule, and length and number of cycles collected during medical record review, regimens were classified into 1 of 14 categories. The first nine categories represent regimens that have supporting clinical efficacy data from clinical research, e.g., cyclophosphamide, methotrexate, and 5-fluorouracil (CMF);3-5 doxorubicin and cyclophosphamide (AC);6, 7 cyclophosphamide, doxorubicin, and 5-fluorouracil (CAF);8-10 and four cycles of doxorubicin (A) followed by six cycles of CMF (A → CMF).11 These regimens are referred to as referenced regimens throughout this report. Categories 10–12 represent regimens that are like the referenced CMF, AC, and CAF regimens in terms of chemotherapy agents but that depart from these regimens in terms of dose, schedule, or cycle duration. Category 13, other, contains infrequently prescribed referenced regimens and combinations of agents or sequential use of agents that depart from known referenced regimens. The last category contains regimens that were changed during the course of chemotherapy. Methods for Calculating Dose Intensity The delivered DI was calculated for each patient to assess the extent to which the actual chemotherapy given achieved the planned DI established by the treating physician (recorded in the medical record). By contrast, in most published reports, the actual chemotherapy delivered is undocumented, with planned DI used as an approximation of delivered DI.13 In studies of community practice, such an approximation may overestimate the actual delivered DI, because it does not reflect common dose modifications and/or failure to complete the planned number of cycles. In addition, because the planned DI also may deviate from the referenced DI, which is based on DI levels reported in clinical trials of the regimen's clinical efficacy, it is important in the current study to evaluate both delivered DI and planned DI relative to the referenced DI. Thus, in this report, relative DI is presented in three ways: planned relative to referenced DI; delivered relative to planned DI; and delivered relative to referenced DI. Two measures of delivered DI were calculated: 1) average relative DI (ARDI)13, 14 and 2) summation DI (SDI).15 ARDI The delivered DI for each drug or agent in a regimen was calculated by summing all of the doses in mg/m2 delivered to a patient over the course of chemotherapy and dividing by the total number of days taken to deliver that chemotherapy, from the first day of the first cycle through the last day of the last cycle. The DI for individual agents was then converted to mg/m2 per week by multiplying by 7. Agent specific relative dose intensities (RDIs) were calculated as a ratio of the delivered DI for that agent to the corresponding referenced dose in mg/m2 per week due if the patient were to receive a full dose on schedule. The delivered ARDI was obtained by averaging the agent specific RDIs delivered in each regimen. SDI The ARDI measure described above does not address variations between regimens with different drug combinations that may have different potencies and efficacies. Hryniuk et al.15 proposed a measure of SDI that relates the DI of single agents in a regimen to the agent DI required to produce a 30% complete or partial response rate in a first-line, single-agent trial in patients with metastatic breast carcinoma. These required doses, measured in mg/m2 per week, are termed unit dose intensity (UDI). SDI was calculated for each referenced regimen and each patient's delivered regimen. The SDI for each of the referenced regimens was obtained by dividing the total referenced DI in mg/m2 per week of each agent by the corresponding UDI and summing across agents. The calculation for delivered SDI was carried out in the same manner described above for the ARDI, but we divided the total dose received in mg/m2 per week for each agent by that agent's UDI. The resulting scale allows for comparison and ranking of patients under different regimens simultaneously taking each agent's efficacy into account and under a simplifying assumption of no interaction effects among the agents. It is important to note that, although ARDI and SDI capture dose delays (DDs) and dose reductions (DRs), they do not capture scheduled cycles of therapy that were not given, because DI is measured over the actual time period taken to deliver chemotherapy. Definitions of DD and DR DDs and DRs are used here as a means for translating DI into practice behaviors. DDs and DRs can be studied as discrete events or cycle-by-cycle to describe the timing of events in the course of chemotherapy and the patterns of recurrence. A DR was defined as a reduction ≥ 15% in any one of the planned primary chemotherapy agents (cyclophosphamide, doxorubicin, methotrexate, or fluorouracil). This was done by calculating the delivered total dose per cycle (in mg) for each agent, dividing by an updated BSA for the cycle (baseline BSA was used when no updates were recorded), and comparing the resulting value for each agent to the planned dose (in mg/m2) for that agent. A DD was defined as a delay ≥ 7 days in the planned start of chemotherapy (beginning with Cycle 2) relative to the start of the previous cycle in all of the primary chemotherapy agents. The planned cycle schedule abstracted from the medical record was used to determine delays. Intracycle delays (for Day 1 and 8 regimens) were not considered. DDs and DRs were determined and counted only for delivered cycles of therapy. Although DDS and DRs of any magnitude influence DI, we limited our analysis to consider only those that represented significant alterations in the planned regimen (e.g., DRs ≥ 15% or DDs ≥ 7 days). Furthermore, by focusing on modifications of planned regimens, we eliminated the effect of planned pretreatment modifications specifically prescribed by the physician to accommodate special patient needs. Neutropenia-Related DDs and DRs Similar to Silber et al.,26 to be considered neutropenia-related, the occurrence of a DD or DR had to meet one of the following conditions: 1) the occurrence was associated with a specific comment in the medical record indicating neutropenia, or 2) when no comment was recorded in the medical record, the DD or DR was proceeded by an episode of FN or a white blood cell count ≤ 2000, an absolute neutrophil count (ANC) ≤ 1000, or a cycle baseline (Day 1) ANC ≤ 1500. Statistical Methods All data analyses were run on SAS software (PC version 6.12; SAS Institute, Cary, NC). Descriptive and summary statistics, including means, medians, ranges, standard deviations, and frequencies, were used to summarize patient characteristics, chemotherapy regimens, dose modifications and DI, and chemotherapy complications. The statistical significance of differences between groups was tested with chi-square tests, t tests, Cochran–Armitage trend tests, or Mantel–Haenszel statistics, as appropriate. RESULTS Patient Characteristics The characteristics of the 1111 study patients are summarized in Table 1. The average patient age was 51.6 years (median, 50 years; standard deviation, 11.0). Ages ranged from 24 years to 86 years, with 49.0% of the sample age < 50 years. The majority of patients were Caucasian (81.1%) and had no comorbid conditions recorded in their medical records (79.0%). In addition, women rarely received radiotherapy prior to chemotherapy (3.9%). Approximately two-thirds of patients (66.0%) were diagnosed with Stage II breast carcinoma. A total of 40.2% of patients had lymph node negative disease, and 41.5% had from one to three positive lymph nodes. Table 1. Distribution of Patient Characteristics Characteristic All patients (n = 1111) No. %aa Values shown are column percentages. Age (yrs) 18–49 541 49.0 50+ 564 51.0 Unknown 6 0.5 Charlson Comorbidity Index 0 926 83.3 1–2 175 15.8 3–4 10 0.9 Stage I 242 22.5 II 709 66.0 III 124 11.5 Unknown 36 3.2 Positive lymph nodes 0 428 40.2 1–3 442 41.5 4–9 118 11.1 10+ 77 7.2 Unknown 46 4.1 XRT prior to Tx 43 3.9 XRT: radiotherapy; Tx: treatment. a Values shown are column percentages. Chemotherapy Regimens and Treatment Year Chemotherapy regimens A total of 24 novel combinations of chemotherapy agents were administered to study patients. The majority of patients (90.2%; 1002 of 1111 patients) received one of the first nine regimens shown in Table 2. These regimens are recognized as referenced adjuvant chemotherapy regimens with supporting efficacy data from clinical research for patients with early-stage breast carcinoma.2-10 Table 2. Frequency and Percent of Sample and Median Summation Dose Intensity for Referenced and Nonreferenced Chemotherapy Regimens in Patients With Early-Stage Breast Carcinoma Regimen Patients/regimen Agents Dose (mg/m2) Route Day(s) of treatment Cycle length (days) No. of cycles Summation dose intensity No. % Referenced regimen Median delivered (Q3 minus Q1)aa Quartile 3 (Q3) minus quartile 1 (Q1). 1 129 12 CMF (P) 28 6 1.86 1.59 (0.37) C 100 PO 1–14 M 40 IV 1, 8 F 600 IV 1, 8 P (40) (PO) (1–14) 2 173 16 CMF 21 8 1.26 1.18 (0.19) C 600 IV 1 M 40 IV 1 F 600 IV 1 3 121 11 CMF 28 6 1.89 1.58 (0.47) C 600 IV 1, 8 M 40 IV 1, 8 F 600 IV 1, 8 4 404 36 AC 21 4 1.91 1.84 (0.17) A 60 IV 1 C 600 IV 1 5 6 < 1 AC 21 5 1.46 1.54 (0.10) A 45 IV 1 C 500 IV 1 6 19 2 FAC 28 6 2.07 1.74 (0.36) F 500 IV 1, 8 A 50 IV 1 C 500 IV 1 7 69 6 CAF 21 8 1.83 1.69 (0.34) C 500 IV 1 A 50 IV 1 F 500 IV 1 8 46 4 CAF 28 6 1.99 1.66 (0.50) C 100 PO 1–14 A 30 IV 1, 8 F 500 IV 1, 8 9bb These regimens were not included in subsequent analyses because of the small sample size. 35 3 A → CMF 1.51 1.39
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