Chemotherapy-Induced Peripheral Neuropathy - Additional Evaluation in Breast Cancer Survivors

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. These regimens generally include taxanes (paclitaxel or docetaxel), which are known to be associated with a considerable risk of chemotherapy-induced peripheral neuropathy (CIPN). CIPN can be quite burdensome for the affected patients. 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 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. 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. To prevent severe neurotoxicity during chemotherapy, the oncology service needs to follow early development of symptoms. In breast cancer patients treated with taxanes, dose reduction due to early development of neuropathy did not change long-term outcomes of toxicity symptoms, suggesting that responses to first doses might be important. In addition, the patient and service burden prohibit frequent out-patient visits to have early detection of toxicity. In clinical neurotoxicity studies a great effort has been put into documenting the validity of grading scales incorporating results from clinical examination with the symptom results. Both approaches require health care resources to document and follow up on CIPN development in order to intervene in the case of severe early toxicity. 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. In a preceding prospective trial, it was shown that the new scoring system can contribute to the identification of moderate to severe CIPN in breast cancer patients who had received taxane-based chemotherapy. The main goal of this trial is to identify the optimal cut-off score of a scoring system to discriminate between mild CIPN and no CIPN in breast cancer survivors previously treated with taxane-based chemotherapy and adjuvant radiotherapy. To identify the optimal cut-off score of a scoring system to discriminate between mild CIPN and no CIPN in breast cancer survivors previously treated with taxane-based chemotherapy and adjuvant radiotherapy. The scores that range between 0 and 44 points are obtained by using a neuropathy tracker. This tracker is based on self-evaluation of symptoms and signs of CIPN by the study participants. The receiver operating characteristic (ROC) curve is used to show the connection between sensitivity and specificity for every possible cut-off for the Scoring System and select the optimal scoring point for detection of mild CIPN. Secondary aims include satisfaction of the study participants with the scoring system and identification of an optimal cut-off score for the Utah Early Neuropathy Scale to discriminate between mild CIPN and no CIPN. Sample size calculation: The main goal of this trial is to identify the optimal cut-off score of a scoring system to discriminate between mild CIPN and no CIPN in breast cancer survivors. The discriminative power of the Scoring System will be assessed by calculating the area under the receiver operating characteristic (ROC) curve (AUC). Sample size is calculated to achieve acceptable precision in the estimation of the AUC measured by means of the 90% confidence interval by incorporating a pre-specified probability, which is referred to as assurance, of achieving the desired lower confidence limit. The following assumptions are made: * The two-sided significance level is set to 10% * An AUC of 0.95 is assumed since this is decided to be an excellent diagnostic accuracy for the Scoring System worth to be considered for future routine use. * The pre-specified lower bound of the confidence interval is assumed to be 0.7. * The assurance probability is set to 80%. * The ratio of standard deviations in patients with no CIPN and patients with mild CIPN is assumed to be 0.67. * Approximately 25% of the patients to be included in this study will have no CIPN (according to standard physical examination and medical history), whereas the other 75% will be clinically diagnosed with mild CIPN, i.e. ratio between negative and positive cases is approximately 0.33. Based on these assumptions above, 26 patients (19 with mild CIPN and 7 without CIPN) are required within the Full Analysis Set. Assuming that roughly 5% of patients will not qualify for Full Analysis Set, a total of 28 patients should be enrolled in the NEURO-BREAC-02 trial. The Full Analysis Set includes all patients who completed the self-assessment of CIPN. Statistical considerations: All data recorded in the case report forms describing the study population (demographic and clinical characteristics recorded at baseline), rates of mild CIPN, and safety will be analyzed descriptively. Categorical data will be presented in contingency tables with frequencies and percentages. Continuous data will be summarized with at least the following: frequency, median, quartiles, mean, standard deviation (standard error), minimum and maximum. Number of patients with protocol deviations during the study and listings describing the deviations will be provided. The data analysis will be performed according to the statistical analysis plan (SAP), and which will be finalized prior to database lock and prior to any statistical analysis.