Identification of Chemotherapy-induced Peripheral Neuropathy

Overview

The main goal of this trial is to identify the optimal cut-off score of a Scoring System to discriminate between moderate to severe chemotherapy-induced peripheral neuropathy (CIPN) and no CIPN in breast cancer survivors previously treated with taxane-based chemotherapy and adjuvant radiotherapy.

Adjuvant radiotherapy is a standard procedure following breast-conserving surgery for non-metastatic breast cancer. Depending of the tumor stage and other risk factors, radiotherapy may be indicated also after mastectomy. A considerable number of these patients receive pre- or postoperative chemotherapy prior to their course of irradiation. These regimens generally include taxanes (paclitaxel or docetaxel), which are known to be associated with a considerable risk of chemotherapy-induced peripheral neuropathy (CIPN). Symptoms of moderate to severe CIPN are defined as limiting instrumental and self-care activities of daily living, respectively. Thus, moderate to severe CIPN can be quite burdensome for the affected patients. We also have concerns, that such distal CIPN might also interfere with dermal integrity at the site of radiation through a more widespread autonomic neuropathy with reduced sudomotor activity. According to three review articles, there is no effective prophylactic treatment to prevent peripheral neuropathy (PNP) in general. Moreover, treatment options for existing PNP are very limited. The only agent shown to be effective to improve symptoms of PNP in a phase 3 trial is duloxetine, a serotonin an nor-epinephrine dual uptake inhibitor. In addition, physiotherapy may contribute to maintaining or improving the patient's gait function. Considering these limited options, it appears important to know risk factors of moderate to severe PNP including CIPN. This knowledge may help identify patients who may benefit from more personalized chemotherapy regimens, Moreover, close monitoring during the treatment is important to be able to adapt the regimen of neurotoxic chemotherapy very soon after the first symptoms of CIPN occur. A Scoring System has been developed by members of our group, which is based on patient reported symptoms and signs from self-examination. Depending on number and severity of symptoms identified by the study participants themselves (self-assessment) with the help of a Neuropathy Tracker, a score ranging between 0 and 44 points is obtained. Prior to this study, the patients had received neoadjuvant or adjuvant taxane-based chemotherapy. The patients will be asked to complete the self-evaluation of symptoms and signs of neuropathy with teh help of a Neuropathy Tracker. which questions symptoms quality, severity and distribution and guide the user through a systematic evaluation of pin-prick from a needle and vibration from the mobile on successive levels from the toes to the knee on both legs. Finally, the extension force or both great toes will be self-assessed by the participant. The self-examination is based on the structure of the Utah Early Neuropathy Score. After completion of the self-assessment of CIPN, the patients will be asked to complete a questionnaire regarding their satisfaction with the Scoring System. The primary aim of the study is to identify the optimal cut-off score of a Scoring System to discriminate between moderate to severe CIPN and no CIPN in breast cancer survivors. The evaluation will be performed in study participants, who based on standard physical examination and medical history were previously classified to have either no or moderate to severe CIPN. Patient-specific values represent the fundamental units for further statistical analyses. First of all, sensitivity and specificity will be estimated for every possible cut-off value of the Scoring System. The Receiver Operating Characteristic (ROC) curve is used to show in a graphical way the connection between sensitivity and specificity. It is defined as the plot of sensitivity versus 1-Specificity (false-positive rate) across varying cut-offs. A ROC curve corresponding to greater discriminant capacity of the Scoring System is located closer to the upper-left-hand corner. The area under the curve (AUC) summarizes the entire location of the ROC curve. The AUC is an effective and combined measure of the sensitivity and specificity that describes the inherent validity of the usefulness of the test in general, where a greater area means a more useful test. If AUC=1 the cut-off score is perfect in the differentiation between subjects with and moderate to severe CIPN and with no CIPN. This happens when the distribution of the score values for the subjects with and without events do not overlap. In contrast, AUC=0.5 means that the Scoring System is performing no better than chance. A rough guide for classifying the accuracy of a diagnostic test is the traditional academic point system (AUCs of 0.5 - 0.6 = fail; 0.6-0.7 poor; 0.7-0.8 = fair, 0.8-0.9 = good and 0.9-1 = excellent). Therefore, any score leading to an AUC of at most 0.7 will be rated insufficiently useful and is not considered worth pursuing. Based on this definition, the following hypothesis system will be subjected to statistical analysis: H0: AUC=0.7 versus H1: AUC ≠0.7. Non-parametric methods for AUC estimation and testing using the normal approximation of the asymptotic properties of the AUC with standard errors will be applied. Technically, the SAS (SAS Institute Inc.) LOGISTIC procedure with the ROCCONTRAST statement can be used to estimate the AUC and its 95% confidence limit and to provide the p-value for the test mentioned above. A significance level of two-sided 10% is prespecified. If statistical significance of the AUC is reached, the most-informative (optimal) scoring point to predict CIPN will be established. Based on discussions with various experts, optimality is defined as a score cut-off value with a sensitivity of at least 90% and a specificity of at least 80%. In addition to this visual selection of a suitable cut-off value, the Youden index (sensitivity + specificity - 1) will be applied to propose an optimal cut-off value for further consideration. As a further sensitivity analysis, the relationship between tertiles of the scores and the incidence of moderate to severe CIPN will be statistically tested using a nonparametric test for ordered differences among groups of score values. It tests the global null hypothesis that the distribution of the response variable does not differ among tertiles. The test is designed to detect alternatives of ordered differences, meaning that the incidence of moderate to severe CIPN increases with the tertiles of score values. In addition, the impact of potential risk factors including smoking history, diabetes, hypertension, autoimmune disease, significant cardiovascular disease, treatment with beta-blockers, age, gender, body mass index, Karnofsky performance score, tumor stage, histology, type of surgery, timing of chemotherapy (neoadjuvant, adjuvant), and type of chemotherapy on the occurrence of moderate to severe CIPN will be evaluated using the Chi-square or the Fisher's exact test. Secondary aim is the satisfaction with the Scoring System, which will be assessed after completion of the self-assessment of symptoms and signs of CIPN by the study participants using the Neuropathy Tracker. Statistical analysis consists of presenting the respective proportions. In case of a dissatisfaction rate \>20%, the Scoring System needs modifications before it can be used in future studies. In case of a dissatisfaction rate \>40%, the Scoring System will be considered not useful.

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Interventions

Eligibility

Outcomes

Central Contacts