Background Data collection and review were identified as major contributors to the cost of randomized clinical trials (RCTs). Purpose We proposed and assessed a novel alternative for long-term clinical trial follow-up based on the data captured through an accredited Cancer Registry (CR) that is part of the National Cancer Database (NCDB). Methods Patients from Mayo Clinic, Rochester, enrolled in the North Central Cancer Treatment Group N934653 (COST) trial (98 patients) and the American College of Surgeons Oncology Group Z0030 trial (55 patients) were included in the study. Demographic, treatment, and long-term outcome data were compared between the hospital-based CR and the RCTs’ databases. Concordances were used to estimate the agreement between two databases. Kaplan—Meier curves were plotted to examine the consistency of time-to-event long-term outcomes of the CR and RCT databases. Results High concordances (>95%) were observed for most demographic and treatment variables between the CR data and RCT data. The vital status concordances were 100% and 94.5% between the CR and COST and Z0030 databases, respectively. Three discrepant death dates were observed, one in the COST trial and two in the Z0030 trial. The concordances of disease-free status between the CR and RCT databases were 99.0% and 87.3%, and 15 discrepant disease recurrence cases were identified: 4 for COST and 11 for Z0030. Limitations The analysis has been focused on patients from a single site, Mayo Clinic, Rochester, enrolled in two large RCT evaluating surgical treatments. The findings herein need to be confirmed in a broader setting, such as multi-center, multi-registry including nonsurgical trials. Conclusions CR data were nearly identical to data from two randomized phase III trials in different disease types and conducted by two different cooperative groups. The NCDB Cancer Registries represent a feasible alternative for obtaining long-term follow-up data for large clinical trials. Clinical Trials 2010; 7: 686—695. http:// ctj.sagepub.com
Evaluation of the Value of Attribution in the Interpretation of Adverse Event Data: A North Central Cancer Treatment Group and American College of Surgeons Oncology Group Investigation
Purpose In March 1998, Common Toxicity Criteria (CTC) version 2.0 introduced the collection of attribution of adverse events (AEs) to study drug. We investigate whether attribution adds value to the interpretation of AE data. Patients and Methods Patients in the placebo arm of two phase III trials—North Central Cancer Treatment Group Trial 97-24-51 (carboxyamino-triazole v placebo in advanced non–small-cell lung cancer) and American College of Surgeons Oncology Group Trial Z9001 (imatinib mesylate v placebo after resection of primary gastrointestinal stromal tumors)—were studied. Attribution was categorized as unrelated (not related or unlikely) and related (possible, probable, or definite). Results In total, 398 patients (84 from Trial 97-24-51 and 314 from Trial Z9001) and 7,736 AEs were included; 47% and 50% of the placebo-arm AEs, respectively, were reported as related. When the same AE was reported in the same patient on multiple visits, the attribution category changed at least once 36% and 31% of the time. AE type and sex (Trial Z9001) and AE type and performance status (Trial 97-24-51) were associated with a higher likelihood of AEs being deemed related. Conclusion Nearly 50% of AEs were reported as attributed to study drug on the placebo arm of two randomized clinical trials. These data provide strong evidence that AE attribution is difficult to determine, unreliable, and of questionable value in interpreting AE data in randomized clinical trials.
Background and Aims. Colorectal cancer, a leading cause of cancer death, is preventable with colonoscopic screening. Colonoscopy cost is high, and optimizing resource utilization for colonoscopy is important. This study’s aim is to evaluate resource allocation for optimal use of facilities for colonoscopy screening. Method. The authors used data from a computerized colonoscopy database to develop a discrete event simulation model of a colonoscopy suite. Operational configurations were compared by varying the number of endoscopists, procedure rooms, the patient arrival times, and procedure room turnaround time. Performance measures included the number of patients served during the clinic day and utilization of key resources. Further analysis included considering patient waiting time tradeoffs as well as the sensitivity of the system to procedure room turnaround time. Results. The maximum number of patients served is linearly related to the number of procedure rooms in the colonoscopy suite, with a fixed room to endoscopist ratio. Utilization of intake and recovery resources becomes more efficient as the number of procedure rooms increases, indicating the potential benefits of large colonoscopy suites. Procedure room turnaround time has a significant influence on patient throughput, procedure room utilization, and endoscopist utilization for varying ratios between 1:1 and 2:1 rooms per endoscopist. Finally, changes in the patient arrival schedule can reduce patient waiting time while not requiring a longer clinic day. Conclusions. Suite managers should keep a procedure room to endoscopist ratio between 1:1 and 2:1 while considering the utilization of related key resources as a decision factor as well. The sensitivity of the system to processes such as turnaround time should be evaluated before improvement efforts are made.
Postoperative Surveillance Recommendations for Early Stage Colon Cancer Based on Results From the Clinical Outcomes of Surgical Therapy Trial
Purpose Intensive postoperative surveillance is associated with improved survival and recommended for patients with late stage (stage IIB and III) colon cancer. We hypothesized that stage I and IIA colon cancer patients would experience similar benefits. Patients and Methods Secondary analysis of data from the Clinical Outcomes of Surgical Therapy trial was performed by analyzing results according to TNM stage; early (stage I and IIA, 537 patients) and late (stage IIB and III, 254 patients) stage disease. Five-year recurrence rates were higher in patients with late (35.7%) versus early stage disease (9.5%). Early and late stage salvage rates, recurrence patterns and methods of first detection were compared by χ2 test. Results Salvage rates for early- and late-stage disease patients with recurrence were the same (35.9% v 37%; P = .9, respectively). Median survival after second surgery after recurrence was 51.2 and 35.8 months for early- and late-stage patients, respectively. Single sites of first recurrence did not significantly differ between early and late stage, but multiple sites of recurrence occurred less often in early-stage patients (3.6% v 28.6%, for early v late, respectively; P < .001). Methods of first detection of recurrence were not significantly different: carcinoembryonic antigen (29.1% v 37.4%), computed tomography scan (23.6% v 26.4%), chest x-ray (7.3% v 12.1%), and colonoscopy (12.7% v 8.8%), for early versus late stage disease, respectively. Conclusion Patients with early-stage colon cancer have similar sites of recurrence, and receive similar benefit from postrecurrence therapy as late-stage patients; implementation of surveillance guidelines for early-stage patients is appropriate.
Impact of Body Mass Index and Weight Change After Treatment on Cancer Recurrence and Survival in Patients With Stage III Colon Cancer: Findings From Cancer and Leukemia Group B 89803
Purpose Obesity is a risk factor for the development of colon cancer. However, the influence of body mass index (BMI) on the outcome of patients with established colon cancer remains uncertain. Moreover, the impact of change in body habitus after diagnosis has not been studied. Patients and Methods We conducted a prospective, observational study of 1,053 patients who had stage III colon cancer and who were enrolled on a randomized trial of adjuvant chemotherapy. Patients reported on height and weight during and 6 months after adjuvant chemotherapy. Patients were observed for cancer recurrence or death. Results In this cohort of patients with stage III cancer, 35% of patients were overweight (BMI, 25 to 29.9 kg/m2), and 34% were obese (BMI ≥ 30 kg/m2). Increased BMI was not significantly associated with a higher risk of colon cancer recurrence or death (P trend = .54). Compared with normal-weight patients (BMI, 21 to 24.9 kg/m2), the multivariate hazard ratio for disease-free survival was 1.00 (95% CI, 0.72 to 1.40) for patients with class I obesity (BMI, 30 to 34.9 kg/m2) and 1.24 (95% CI, 0.84 to 1.83) for those with class II to III obesity (BMI ≥ 35 kg/m2) after analysis was adjusted for tumor-related prognostic factors, physical activity, tobacco history, performance status, age, and sex. Similarly, after analysis was controlled for BMI, weight change (either loss or gain) during the time period between ongoing adjuvant therapy and 6 months after completion of therapy did not significantly impact on cancer recurrence and/or mortality. Conclusion Neither BMI nor weight change was significantly associated with an increased risk of cancer recurrence and death in patients with colon cancer.