How Many Cancer Clinical Trials Can a Clinical Research Coordinator Manage? The Clinical Research Coordinator Workload Assessment Tool.

PURPOSE: Cancer clinical trials (CTs) are now more complex than ever before and require dedicated personnel (clinical research coordinators [CRCs]) to perform regulatory and administrative activities and protocol- and patient-related procedures. We developed a simple tool to measure the workload (WL) of CRCs involved in cancer research and to estimate personnel requirements within a Clinical Trial Center. METHODS: A literature review and 2-month period in which CRCs recorded their activities in a diary provided valuable information that led to the Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori Workload Assessment Tool (IWAT) being divided into three sections: Protocol, On-Treatment Patients, and Follow-Up Patients. Twelve full-time senior CRCs from three sites of the Network measured their monthly WL for 30 months to evaluate IWAT reproducibility and accuracy. RESULTS: The IWAT proved to be a user-friendly tool (3-6 minutes required for each CT), with high reproducibility (interobserver reproducibility ranged from 82% to 100% for each IWAT item). In December 2017, the Network had 185 ongoing CTs, with a median of 2.5 active centers for each CT. On the basis of 448 total IWAT measures by CRCs, the majority of trials were academic (57%) or dealt with advanced disease (77%). The median IWAT WL score for each study was 20.98 ± 22.90 (range, 2-188) and 475 ± 229 (range, 150 [junior staff] - 930 [extreme heavy WL]) for each CRC. On the basis of our experience, a monthly WL score of 500-600 was considered an appropriate value for a full-time CRC. CONCLUSION: The IWAT could prove useful in evaluating CT complexity, estimating appropriate CRC WLs, and defining personnel requirements. Independent validation by other CRCs working in different organizational contexts and in different countries is needed.

Appropriate use of tumour biomarkers for treatment with innovative drugs: A retrospective study.

Performing randomised clinical trials to address the clinical usefulness of predictive and prognostic tumour markers is a complex process for several reasons, and observational experiences may thus play an important role. The present study performed an observational retrospective analysis in Area Vasta Romagna, Italy, collecting information on tumour marker determination in 760 consecutive patients who started a new line of anticancer therapy between January and June 2010. The determination of well-known biomarkers was requested for all gastrointestinal stromal tumour (GIST) patients (n=13) and for almost all breast cancer patients (n=369), and targeted therapies were consequently prescribed. Conversely, Kirsten rat sarcoma viral oncogene homolog (KRAS) determination in colon cancer patients (n=177) was requested in ~50% of advanced cases, while epidermal growth factor receptor (EGFR) determination was required in slightly more than 30% of the same patients. EGFR and KRAS determinations were requested in only 15% and 7.5% of non-small cell lung cancer (NSCLC) patients (n=201), respectively. There would appear to be greater appropriateness of tumour marker determination for breast cancer and GISTs than for colon cancer and NSCLC. Resources can be further optimised by standardising tumour marker determinations in terms of the timing of requests and the consequent use of the results for tailored treatment planning.

The palliative prognostic score and survival in patients with advanced solid tumors receiving chemotherapy.

PURPOSE: To evaluate the accuracy of the Palliative Prognostic Score (PaP score) in selecting metastatic gastrointestinal or nonsmall-cell lung cancer patients candidate to palliative chemotherapy. MATERIALS AND METHODS: The PaP score was calculated in 173 patients with advanced, pretreated gastrointestinal or nonsmall-cell lung cancer before starting a further line of chemotherapy with palliative aim. Symptom distress score was calculated using the Edmonton Symptom Assessment System (ESAS) before every course of chemotherapy. Univariate analysis of survival was performed using the logrank test; multivariate analysis was performed using the Cox regression model. Symptom distress scores were compared using multivariate analysis of variance test for repeated measures, and overall symptom distress score was compared using analysis of variance test for repeated measures. RESULTS: Overall median survival was 26 weeks; in PaP score class A it was 32 weeks, and in class B 8 weeks (p < 0.0001). No patient was classified in class C. The two-class PaP score resulted in an independent prognostic factor (p = 0.022), as well as Karnofsky performance status (p = 0.002) and colorectal cancer (p = 0.017). A trend towards worsening of symptom distress was observed in the entire population and in class A. The high number of missed data did not permit an adequate analysis in class B. CONCLUSIONS: The PaP score seems to discriminate patients who could benefit by palliative chemotherapy from those who could better benefit by supportive and palliative approach. However, the data are insufficient to validate the use of the PaP score in patients to be treated with palliative chemotherapy, and further trials should be planned to assess its ability to improve the quality of care in oncology and the appropriateness in the choice of palliative chemotherapy.