Pharmacokinetically based dosing of weekly paclitaxel to reduce drug-related neurotoxicity based on a single sample strategy

Paclitaxel therapeutic drug monitoring - International association of therapeutic drug monitoring and clinical toxicology recommendations

Paclitaxel, one of the most frequently used anticancer drugs, is dosed by body surface area, which leads to substantial inter-individual variability in systemic drug exposure. We evaluated clinical evidence regarding the scientific rationale and clinical benefit of individualized paclitaxel dosing based on measured systemic concentrations, known as therapeutic drug monitoring (TDM). In retrospective studies, higher systemic exposure is associated with greater toxicity and efficacy of paclitaxel treatment across several disease types and dosing regimens. In prospective trials, TDM reduces variability in systemic exposure, and has been demonstrated to reduce toxicity while retaining treatment efficacy for 3-weekly dosing in patients with advanced non-small cell lung cancer. Despite the demonstrated benefits of paclitaxel TDM, clinical adoption has been limited due to the challenges with sample collection and analysis. Based on our review, we strongly recommend TDM for patients receiving every 3-week paclitaxel in combination with a platinum agent for advanced NSCLC, due to the prospectively demonstrated clinical benefits, and find moderate evidence to recommend TDM for paclitaxel 3-hour infusions for other tumor types and preliminary evidence suggesting potential usefulness for paclitaxel administered by 1-hour infusions.

Paclitaxel and Therapeutic Drug Monitoring with Microsampling in Clinical Practice

Paclitaxel is an anticancer agent efficacious in various tumors. There is large interindividual variability in drug plasma concentrations resulting in a wide variability in observed toxicity in patients. Studies have shown the time the concentration of paclitaxel exceeds 0.05 µM is a predictive parameter of toxicity, making dose individualization potentially useful in reducing the adverse effects. To determine paclitaxel drug concentration, a venous blood sample collected 24 h following the end of infusion is required, often inconvenient for patients. Alternatively, using a microsampling device for self-sampling would facilitate paclitaxel monitoring regardless of the patient's location. We investigated the feasibility of collecting venous and capillary samples (using a Mitra® device) from cancer patients to determine the paclitaxel concentrations. The relationship between the venous plasma and whole blood and venous and capillary blood (on Mitra®) paclitaxel concentrations, defined by a Passing-Bablok regression, were 0.8433 and 0.8569, respectively. Demonstrating a clinically acceptable relationship between plasma and whole blood paclitaxel concentration would reduce the need to establish new target concentrations in whole blood. However, in this study, comparison of venous and capillary blood using Mitra® for sampling displayed wide confidence intervals suggesting the results from the plasma and whole blood on this device may not be interchangeable.

Paclitaxel exposure-toxicity analysis reveals a pharmacokinetic determinant for dose-limiting neutropenia in East-Asian solid tumor patients: results from two prospective, phase II studies

PURPOSE

The time of a paclitaxel (PTX) concentration remains above 0.05 μM (Tc > 0.05) has been associated with PTX-induced adverse effects in Caucasians, while limited studies were reported in Asians. This study was aimed to explore the characteristics of Tc > 0.05 and the relationship between PTX exposure and toxicity in East-Asian patients.

METHODS

This study was based on two prospective phase II clinical trials and patients with advanced nasopharyngeal cancer (NPC) and non-small cell lung cancer (NSCLC) who were naïve to PTX were included independently. Eligible patients receive PTX (175 mg/m²) and carboplatin (AUC = 5) treatment every 3 weeks. PTX pharmacokinetic analysis was accessed. The relationship between PTX exposure and toxicities after first cycle as well as clinical efficacy was evaluated.

RESULTS

A total of 93 NPC and 40 NSCLC patients were enrolled. PTX exposure was consistent in two trials with average Tc > 0.05 duration of 38.8 h and 38.4 h, respectively. Average Tc > 0.05 in patients with grade 3/4 neutropenia was significantly higher than those without severe neutropenia in NPC patients (P = 0.003) and NSCLC patients (P = 0.007). Cut-off value of Tc > 0.05 were identified from the NPC cohort and then verified in the NSCLC cohort, dividing patients into high exposure Tc > 0.05 group (> 39 h) and low exposure group (≤ 39 h). Incidence of grade 3/4 neutropenia were significantly higher in the high exposure group in NPC cohort (43.3% vs 10.0%, P < 0.001) and NSCLC cohort (42.1% vs 9.5%, P = 0.028). No significant relationship between Tc > 0.05 and efficacy were observed.

CONCLUSION

Patients with PTX Tc > 0.05 duration above 39 h experience more severe neutropenia than those under 39 h. Prospective studies are needed to verify this threshold.

Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review

Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key use cases in which artificial intelligence (AI) could be leveraged to reduce the frequency of ADEs. We focused on modern machine learning techniques and natural language processing. 78 articles were included in the scoping review. Studies were heterogeneous and applied various AI techniques covering a wide range of medications and ADEs. We identified several key use cases in which AI could contribute to reducing the frequency and consequences of ADEs, through prediction to prevent ADEs and early detection to mitigate the effects. Most studies (73 [94%] of 78) assessed technical algorithm performance, and few studies evaluated the use of AI in clinical settings. Most articles (58 [74%] of 78) were published within the past 5 years, highlighting an emerging area of study. Availability of new types of data, such as genetic information, and access to unstructured clinical notes might further advance the field.

The Influence of Body Composition on the Systemic Exposure of Paclitaxel in Esophageal Cancer Patients

Changes in body composition are associated with chemotherapy-related toxicities and effectiveness of treatment. It is hypothesized that the pharmacokinetics (PK) of chemotherapeutics may depend on body composition. The effects of body composition on the variability of paclitaxel PK were studied in patients with esophageal cancer. Skeletal muscle index (SMI), visceral adipose tissue (VAT), and skeletal muscle density (SMD) were measured at the third lumbar vertebra on computed tomography (CT) scans performed before treatment. Paclitaxel PK data were collected from a prospective study performed between May 2004 and January 2014. Non-linear mixed-effects modeling was used to fit paclitaxel PK profiles and evaluate the covariates body surface area (BSA), SMI, VAT, and SMD using a significance threshold of p < 0.001. Paclitaxel was administered to 184 patients in a dose range of 50 to 175 mg/m². Median BSA was 1.98 m² (range of 1.4 to 2.8 m²). SMI, VAT, and SMD were not superior to BSA in predicting paclitaxel PK. The additive value of SMI, VAT, and SMD to BSA was also negligible. We did not find evidence that paclitaxel dosing could be further optimized by correcting for SMI, VAT, or SMD.

Time-to-Event Analysis of Paclitaxel-Associated Peripheral Neuropathy in Advanced Non-Small-Cell Lung Cancer Highlighting Key Influential Treatment/Patient Factors

Paclitaxel-associated peripheral neuropathy (PN), a major dose-limiting toxicity, significantly impacts patients' quality of life/treatment outcome. Evaluation of risk factors often ignores time of PN onset, precluding the impact of time-dependent factors, e.g., drug exposure, needed to comprehensively characterize PN. We employed parametric time-to-event (TTE) analysis to describe the time course of risk of first occurrence of clinically relevant PN grades ≥2 (PN2+, n = 105, common terminology criteria v4.0) and associated patient/treatment characteristics, leveraging data from 365 patients (1454 cycles) receiving paclitaxel every 3 weeks (plus carboplatin AUC = 6 or cisplatin 80 mg/m2) for ≤6 cycles. Paclitaxel was intravenously administered (3 hours) as standard 200-mg/m2 doses (n = 182) or as pharmacokinetic-guided dosing (n = 183). A cycle-varying hazard TTE model linking surge in hazard of PN2+ to paclitaxel administration [PN2+ proportions (i.e., cases per 1000 patients), 1st day, cycle 1: 4.87 of 1000; cycle 6: 7.36 of 1000] and linear decline across cycle (last day, cycle 1: 1.64 of 1000; cycle 6: 2.48 of 1000) adequately characterized the time-varying hazard of PN2+. From joint covariate evaluation, PN2+ proportions (1st day, cycle 1) increased by 1.00 per 1000 with 5-μmol·h/l higher paclitaxel exposure per cycle (AUC between the start and end of a cycle, most relevant covariate), 0.429 per 1000 with 5-year higher age, 1.31 per 1000 (smokers vs. nonsmokers), and decreased by 0.670 per 1000 (females vs. males). Compared to 200 mg/m2 dosing every 3 weeks, model-predicted cumulative risk of PN2+ was significantly higher (42%) with 80 mg/m2 weekly dosing but reduced by 11% with 175 mg/m2 dosing every 3 weeks. The established TTE modeling framework enables quantification and comparison of patient's cumulative risks of PN2+ for different clinically relevant paclitaxel dosing schedules, sparing patients PN2+ to improve paclitaxel therapy. SIGNIFICANCE STATEMENT: Characterization of risk factors of paclitaxel-associated peripheral neuropathy (PN) typically involves time-independent comparison of PN odds in patient subpopulations, concealing the impact of time-dependent factors, e.g., changing paclitaxel exposure, required to comprehensively characterize PN. We developed a parametric time-to-event model describing the time course in risk of clinically relevant paclitaxel-associated PN, identifying the highest risk in older male smokers with higher paclitaxel area under the plasma concentration-time curve between the start and end of a cycle. The developed framework enabled quantification of patient's risk of PN for clinically relevant paclitaxel dosing schedules, facilitating future dosing decisions.

Personalized Management of Chemotherapy-Induced Peripheral Neuropathy Based on a Patient Reported Outcome: CALGB 40502 (Alliance)

Chemotherapy-induced peripheral neuropathy (henceforth, neuropathy) is often dose limiting and is generally managed by empirical dose modifications. We aimed to (1) identify an early time point that is predictive of future neuropathy using a patient-reported outcome and (2) propose a dose-adjustment algorithm based on simulated data to manage neuropathy. In previous work, a dose-neuropathy model was developed using dosing and patient-reported outcome data from Cancer and Leukemia Group B 40502 (Alliance), a randomized phase III trial of paclitaxel, nanoparticle albumin-bound paclitaxel or ixabepilone as first-line chemotherapy for locally recurrent or metastatic breast cancer. In the current work, an early time point that is predictive of the future severity of neuropathy was identified based on predictive accuracy of the model. Using the early data and model parameters, simulations were conducted to propose a dose-adjustment algorithm for the prospective management of neuropathy in individual patients. The end of the first 3 cycles (12 weeks) was identified as the early time point based on a predictive accuracy of 75% for the neuropathy score after 6 cycles. For paclitaxel, nanoparticle albumin-bound paclitaxel, and ixabepilone, simulations with the proposed dose-adjustment algorithm resulted in 61%, 48%, and 35% fewer patients, respectively, with neuropathy score ≥8 after 6 cycles compared to no dose adjustment. We conclude that early patient-reported outcome data on neuropathy can be used to guide dose adjustments in individual patients that reduce the severity of future neuropathy. Prospective validation of this approach should be undertaken in future studies.

Does Older Age Lead to Higher Risk for Neutropenia in Patients Treated with Paclitaxel?

PURPOSE

There is ongoing concern regarding increased toxicity from paclitaxel in elderly patients, particularly of severe neutropenia. Yet, data so far is controversial and this concern is not supported by a clinically relevant age-dependent difference in pharmacokinetics (PK) of paclitaxel. This study assessed whether age is associated with increased risk for paclitaxel-induced neutropenia.

METHODS

Paclitaxel plasma concentration-time data, pooled from multiple different studies, was combined with available respective neutrophil count data during the first treatment cycle. Paclitaxel pharmacokinetic-pharmacodynamic (PK-PD) data was modeled using a non-linear mixed effects approach and a semiphysiological neutropenia model, where systemic paclitaxel exposure was linked to reduced proliferation of neutrophils. The impact of age was evaluated on relevant variables in the model, using a significance threshold of p < 0.005.

RESULTS

Paclitaxel PK-PD data was evaluated from 300 patients, with a median age of 65 years (range 23-84 years), containing 116 patients ≥70 years (39%). First cycle neutrophil counts were adequately described by a threshold effect model of paclitaxel on the proliferation rate of neutrophils. Age as a continuous or dichotomous variable (≥70 versus <70 years) did not significantly impact sensitivity of the bone marrow to paclitaxel nor the average maturation time of neutrophils (both p > 0.005), causing a decline in the respective interindividual variability of <1%.

CONCLUSION

Results from this large retrospective patient cohort do not suggest elderly patients to be at an increased risk of developing paclitaxel-associated neutropenia during the first treatment cycle. Reflexive dose reductions of paclitaxel in elderly patients are unlikely to improve the risk of severe neutropenia and may be deleterious.

Does nab-paclitaxel have a higher incidence of peripheral neuropathy than solvent-based paclitaxel? Evidence from a systematic review and meta-analysis

Paclitaxel-induced peripheral neuropathy is a common reason for dose reduction or early cessation of therapy. Nab-paclitaxel was developed to provide additional clinical benefits and overcome the safety drawbacks of solvent-based paclitaxel. However, the incidence of peripheral neuropathy induced by nab-paclitaxel was reported higher than solvent-based paclitaxel but evidence remains inconsistent. Therefore, we conducted a meta-analysis to compare the incidence and severity of peripheral neuropathy between nab-paclitaxel and solvent-based paclitaxel mono-chemotherapy. In total, 24 articles were included in this meta-analysis. Results revealed the incidence of peripheral neuropathy induced by nab-paclitaxel was higher than solvent-based paclitaxel. The dosage and assessment method could influence the comparison of the incidence and severity of peripheral neuropathy between nab-paclitaxel and solvent-based paclitaxel. Current evidence suggests the incidence of peripheral neuropathy induced by nab-paclitaxel was higher than solvent-based paclitaxel among cancer patients received mono-chemotherapy. When received nab-paclitaxel, more attention should be paid to peripheral neuropathy.

Quantitation of paclitaxel, and its 6-alpha-OH and 3-para-OH metabolites in human plasma by LC-MS/MS

We have developed a high performance liquid chromatography mass spectrometry method for quantitating paclitaxel and its 6-alpha-OH and 3-para-OH metabolites in 0.1 mL human plasma. After MTBE liquid-liquid extraction, chromatographic separation was achieved with a Phenomenex synergy polar reverse phase (4 μm, 2 mm × 50 mm) column and a gradient of 0.1% formic acid in acetonitrile and water over an 8 min run time. Mass spectrometric detection was performed on an ABI SCIEX 4000Q with electrospray, positive-mode ionization. The assay was linear from 10-10,000 ng/mL for paclitaxel and 1-1000 ng/mL for both metabolites and proved to be accurate (94.3-110.4%) and precise (<11.3%CV). Recovery from plasma was 59.3-91.3% and matrix effect was negligible (-3.5 to 6.2%). Plasma freeze thaw stability (90.2-107.0%), stability for 37 months at -80 °C (89.4-112.6%), and stability for 4 h at room temperature (87.7-100.0%) were all acceptable. This assay will be an essential tool to further define the metabolism and pharmacology of paclitaxel and metabolites in the clinical setting. The assay may be utilized for therapeutic drug monitoring of paclitaxel and may also reveal the CYP2C8 and CYP3A4 activity phenotype of patients.

Impact of Older Age on the Exposure of Paclitaxel: a Population Pharmacokinetic Study

PURPOSE

Limited available data suggest that older patients are more prone to develop paclitaxel-induced toxicity than their younger peers. It remains unclear whether this is related to age-dependent pharmacokinetics (PK) of paclitaxel. Primary objective of this study was to determine the influence of older age on the PK of paclitaxel.

METHODS

PK data of patients aged ≥70 years who received paclitaxel intravenously at the Netherlands Cancer Institute (NKI) and the Radboud University Medical Center between September 2012 and May 2017 were collected. These prospectively collected data were pooled with previously published databases from multiple clinical trials conducted at the NKI and Erasmus MC Cancer Institute. A previously developed 3-compartment population PK model with saturable distribution and elimination was used to describe paclitaxel plasma concentration-time data. Hereafter, influence of age on paclitaxel PK was assessed in a previously established full covariate model.

RESULTS

In total, paclitaxel PK data from 684 patients were available, consisting of 166 patients ≥70 years (24%). Median age of the cohort was 61 years (range 18 to 84 years). The impact of age, either treated as a continuous or dichotomous covariate (<70 versus ≥70 years), on the elimination of paclitaxel was only marginal but statistically significant (both p < 0.001 with no clinically relevant decrease in interindividual variability). For a typical patient, maximal elimination capacity decreased by only 5% for a 10-year increment of age.

CONCLUSION

In this extensive multi-center dataset, which included a considerable number of older patients, older age had no clinically relevant impact on paclitaxel PK.

Patients carrying CYP2C8*3 have shorter systemic paclitaxel exposure

AIM

First, evaluate if patients carrying putatively diminished activity CYP2C8 genotype have longer paclitaxel exposure (e.g., time above threshold concentration of 0.05 μM [T_{c >0.05}]). Second, screen additional pharmacogenes for associations with T_{c >0.05}. Methods: Pharmacogene panel genotypes were translated into genetic phenotypes for associations with T_{c >0.05} (n = 58).

RESULTS

Patients with predicted low-activity CYP2C8 had shorter T_{c >0.05} after adjustment for age, body surface area and race (9.65 vs 11.03 hrs, β = 5.47, p = 0.02). This association was attributed to CYP2C8*3 (p = 0.006), not CYP2C8*4 (p = 0.58). Patients with predicted low-activity SLCO1B1 had longer T_{c >0.05} (12.12 vs 10.15 hrs, β = 0.85, p = 0.012).

CONCLUSION

Contrary to previous publications, CYP2C8*3 may confer increased paclitaxel metabolic activity. SLCO1B1 and CYP2C8 genotype may explain some paclitaxel pharmacokinetic variability.

Validation of a Commercial Assay and Decision Support Tool for Routine Paclitaxel Therapeutic Drug Monitoring (TDM)

BACKGROUND

The value of therapeutic drug monitoring (TDM) for paclitaxel (PTX) was recently demonstrated in the largest TDM trial ever conducted in oncology. The trial demonstrated significant reduction in neuropathy when using TDM. Dose adjustment for PTX was based on time above a threshold concentration (Tc>0.05). Tc>0.05 must be calculated with a pharmacokinetic model and complex nonlinear mixed-effects software. The use of the software and chromatographic methods to measure PTX requires specialized expertise. User-friendly methods to quantitate PTX and calculate Tc>0.05 could simplify the introduction of TDM into routine clinical practice.

METHODS

The immunoassay (MyPaclitaxel) was used to quantitate PTX in samples from the clinical trial; the results were used to calculate Tc>0.05 using a stand-alone computer program with a simple, friendly graphical user interface for nonlinear mixed-effects pharmacokinetic calculations (MyCare Drug Exposure Calculator). The resulting dose recommendations from the calculated Tc>0.05 were compared with those using liquid chromatography-ultraviolet detection and NONMEM to examine the efficacy of the simpler tools for TDM.

RESULTS

There was a good agreement between the immunoassay and liquid chromatography-ultraviolet detection: Passing-Bablok regression slope was 1.045 and intercept was -6.00, R was 0.9757, and mean bias was -1.77 ng/mL (-2.07 nmol/L). Dosing recommendations were identical for 70% of the cycles and within 10% for 89% of the samples. All Tc>0.05 values were at the same or adjacent medical decision points.

CONCLUSIONS

MyPaclitaxel assay and MyCare Drug Exposure Calculator are convenient, user-friendly tools that may be suitable for routine TDM of PTX in clinical care.

Paclitaxel Plasma Concentration after the First Infusion Predicts Treatment-Limiting Peripheral Neuropathy

Purpose: Paclitaxel exposure, specifically the maximum concentration (C_max) and amount of time the concentration remains above 0.05 μmol/L (T_c>0.05), has been associated with the occurrence of paclitaxel-induced peripheral neuropathy. The objective of this study was to validate the relationship between paclitaxel exposure and peripheral neuropathy.Experimental Design: Patients with breast cancer receiving paclitaxel 80 mg/m² × 12 weekly doses were enrolled in an observational clinical study (NCT02338115). Paclitaxel plasma concentration was measured at the end of and 16-26 hours after the first infusion to estimate C_max and T_c>0.05 Patient-reported peripheral neuropathy was collected via CIPN20 at each dose, and an 8-item sensory subscale (CIPN8) was used in the primary analysis to test for an association with T_c>0.05 Secondary analyses were conducted using C_max as an alternative exposure parameter and testing each parameter with a secondary endpoint of the occurrence of peripheral neuropathy-induced treatment disruption.Results: In 60 subjects included in the analysis, the increase in CIPN8 during treatment was associated with baseline CIPN8, cumulative dose, and relative dose intensity (P < 0.05), but neither T_c>0.05 (P = 0.27) nor C_max (P = 0.99). In analyses of the secondary endpoint, cumulative dose (OR = 1.46; 95% confidence interval (CI), 1.18-1.80; P = 0.0008) and T_c>0.05 (OR = 1.79; 95% CI, 1.06-3.01; P = 0.029) or C_max (OR = 2.74; 95% CI, 1.45-5.20; P = 0.002) were associated with peripheral neuropathy-induced treatment disruption.Conclusions: Paclitaxel exposure is predictive of the occurrence of treatment-limiting peripheral neuropathy in patients receiving weekly paclitaxel for breast cancer. Studies are warranted to determine whether exposure-guided dosing enhances treatment effectiveness and/or prevents peripheral neuropathy in these patients. Clin Cancer Res; 24(15); 3602-10. ©2018 AACR.

In Silico Evaluation of Pharmacokinetic Optimization for Antimitogram-Based Clinical Trials

Antimitograms are prototype in vitro tests for evaluating chemotherapeutic efficacy using patient-derived primary cancer cells. These tests might help optimize treatment from a pharmacodynamic standpoint by guiding treatment selection. However, they are technically challenging and require refinements and trials to demonstrate benefit to be widely used. In this study, we performed simulations aimed at exploring how to validate antimitograms and how to complement them by pharmacokinetic optimization. A generic model of advanced cancer, including pharmacokinetic-pharmacodynamic monitoring, was used to link dosing schedules with progression-free survival (PFS), as built from previously validated modules. This model was used to explore different possible situations in terms of pharmacokinetic variability, pharmacodynamic variability, and antimitogram performance. The model recapitulated tumor dynamics and standalone therapeutic drug monitoring efficacy consistent with published clinical results. Simulations showed that combining pharmacokinetic and pharmacodynamic optimization should increase PFS in a synergistic fashion. Simulated data were then used to compute required clinical trial sizes, which were 30% to 90% smaller when pharmacokinetic optimization was added to pharmacodynamic optimization. This improvement was observed even when pharmacokinetic optimization alone exhibited only modest benefit. Overall, our work illustrates the synergy derived from combining antimitograms with therapeutic drug monitoring, permitting a disproportionate reduction of the trial size required to prove a benefit on PFS. Accordingly, we suggest that strategies with benefits too small for standalone clinical trials could be validated in combination in a similar manner.Significance: This work offers a method to reduce the number of patients needed for a clinical trial to prove the hypothesized benefit of a drug to progression-free survival, possibly easing opportunities to evaluate combinations. Cancer Res; 78(7); 1873-82. ©2018 AACR.

Long-Term Effects, Pathophysiological Mechanisms, and Risk Factors of Chemotherapy-Induced Peripheral Neuropathies: A Comprehensive Literature Review

Neurotoxic anticancer drugs, such as platinum-based anticancer drugs, taxanes, vinca alkaloids, and proteasome/angiogenesis inhibitors are responsible for chemotherapy-induced peripheral neuropathy (CIPN). The health consequences of CIPN remain worrying as it is associated with several comorbidities and affects a specific population of patients already impacted by cancer, a strong driver for declines in older adults. The purpose of this review is to present a comprehensive overview of the long-term effects of CIPN in cancer patients and survivors. Pathophysiological mechanisms and risk factors are also presented. Neurotoxic mechanisms leading to CIPNs are not yet fully understood but involve neuronopathy and/or axonopathy, mainly associated with DNA damage, oxidative stress, mitochondria toxicity, and ion channel remodeling in the neurons of the peripheral nervous system. Classical symptoms of CIPNs are peripheral neuropathy with a “stocking and glove” distribution characterized by sensory loss, paresthesia, dysesthesia and numbness, sometimes associated with neuropathic pain in the most serious cases. Several risk factors can promote CIPN as a function of the anticancer drug considered, such as cumulative dose, treatment duration, history of neuropathy, combination of therapies and genetic polymorphisms. CIPNs are frequent in cancer patients with an overall incidence of approximately 38% (possibly up to 90% of patients treated with oxaliplatin). Finally, the long-term reversibility of these CIPNs remain questionable, notably in the case of platinum-based anticancer drugs and taxanes, for which CIPN may last several years after the end of anticancer chemotherapies. These long-term effects are associated with comorbidities such as depression, insomnia, falls and decreases of health-related quality of life in cancer patients and survivors. However, it is noteworthy that these long-term effects remain poorly studied, and only limited data are available such as in the case of bortezomib and thalidomide-induced peripheral neuropathy.