Skip to main content

Comorbidities and Risk of Chemotherapy-Induced Peripheral Neuropathy Among Participants 65 Years or Older in Southwest Oncology Group Clinical Trials

Publication: Journal of Clinical Oncology
PDF

Abstract

Background

Neuropathy is a debilitating toxicity associated with various chemotherapy agents. We evaluated the association between common comorbid conditions and the development of peripheral neuropathy in patients treated with taxane-based chemotherapy.

Methods

We examined the Southwest Oncology Group database to identify phase II and III trials that included taxane therapy from 1999 to 2011. We linked the Southwest Oncology Group clinical records to Medicare claims data according to Social Security number, sex, and date of birth. The following disease conditions potentially associated with peripheral neuropathy were evaluated: diabetes, hypothyroidism, hypercholesterolemia, hypertension, varicella zoster, peripheral vascular disease, and autoimmune diseases. Multivariate logistic regression was used to model the odds of experiencing grade 2 to 4 neuropathy.

Results

A total of 1,401 patients from 23 studies were included in the analysis. Patients receiving paclitaxel were more likely to experience grade 2 to 4 neuropathy compared with docetaxel (25% v 12%, respectively; OR, 2.20; 95% CI, 1.52 to 3.18; P < .001). The inclusion of a platinum agent was also associated with greater neuropathy (OR, 1.68; 95% CI, 1.18 to 2.40; P = .004). For each increase in age of 1 year, the odds of neuropathy increased 4% (P = .006). Patients with complications from diabetes had more than twice the odds of having neuropathy (OR, 2.13; 95% CI, 1.31 to 3.46; P = .002) compared with patients with no diabetes. In contrast, patients with autoimmune disease were half as likely to experience neuropathy (OR, 0.49; 95% CI, 0.24 to 1.02; P = .06). The other conditions were not associated with neuropathy.

Conclusion

We found that in addition to drug-related factors, age and history of diabetes were independent predictors of the development of chemotherapy-induced peripheral neuropathy. Interestingly, we also observed that a history of autoimmune disease was associated with reduced odds of neuropathy. Patients with diabetic complications may choose to avoid paclitaxel or taxane plus platinum combination therapies if other efficacious options exist.

Introduction

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating toxicity associated with various agents that are widely used in the treatment of cancer. These toxicities have a significant impact on quality of life. Clinical trials with taxanes have shown grade 2 to 4 neuropathy rates ranging from 15% to 23%, as graded by the Common Terminology Criteria Adverse Events system, with higher rates related to the specific drug, dose, schedule, and therapy duration.1-3 Patients with grade 2 neuropathy have interference with function (eg, difficulty buttoning a shirt), those with grade 3 have interference with activities of daily living (eg, brushing teeth), and those with grade 4 have permanent and disabling symptoms.
There are a paucity of effective therapies for the treatment and prevention of CIPN.4 Identifying patients at risk for CIPN is important for multiple reasons. First, it can assist with personalizing regimens on the basis of toxicity risk. Also, understanding factors that contribute to risk may point to potential underlying mechanisms that can be targeted for CIPN treatment or prevention trials.
The majority of studies evaluating risk factors for CIPN have been retrospective, from a single institution, or with inconsistent definitions of CIPN. Initial studies suggested that race, age, and obesity are risk factors for CIPN; however, other studies have not confirmed these findings.5-11 It also may be that a history of other conditions that predispose patients to peripheral neuropathy may result in an increased risk of developing CIPN. A comprehensive evaluation of preexisting diseases or disorders associated with peripheral neuropathy, such as hypothyroidism, varicella zoster, and autoimmune disease, has not been reported.
Using a novel linkage between elderly patients enrolled in Southwest Oncology Group (SWOG) and Medicare claims data, we examined whether specific demographic, clinical, treatment, and comorbid disease conditions at the start of therapy predicted the development of CIPN among patients age 65 years or older enrolled in clinical trials containing taxane-based therapy.

Methods

The study data were from SWOG, a national clinical trials consortium. We systematically identified all phase II and phase III trials that included taxane therapy in one or more treatment arms from 1999 to 2011 (inclusive) and that had already published their primary study report. Patients in trials for lung, prostate, breast, head and neck, bladder, and ovarian cancer were included. Patients who did not receive taxane therapy were excluded.

Demographic, Clinical, Treatment, and Neuropathy Data

Patient demographic characteristics, such as age, self-reported race and ethnicity, and sex, were based on questionnaires administered at the time of initial trial enrollment. A prognostic risk variable for survival outcomes was created on the basis of the clinical risk factors identified for each study (Appendix Table A1, online only). Within each study, an outcomes risk score was calculated for each patient as the sum of the number of study-specific adverse risk factors. The risk score was then split at the median, creating an indicator variable for high risk versus low risk. This allowed for risk adjustment for clinical prognosis in a uniform manner across the diverse panel of studies.
Baseline predictors of interest for CIPN were the type of taxane therapy, the planned duration of therapy, and the receipt of any platinum treatment on the basis of protocol-specified planned treatment. The actual observed amount of taxane therapy was examined separately, although it was not included as a model covariate because patients who develop CIPN may stop therapy prematurely. Time of initial registration, split at the halfway point through the period, and observed time on taxane treatment (split at the median) were collected as part of the study protocol. Clinical neuropathy was collected for each study as part of study protocol acute treatment toxicity reporting. Toxicity grades were defined by Common Terminology Criteria Adverse Events (version 2.0). Neuropathy may have occurred at any time during the study. The highest grade reported was the one retained as the neuropathy outcome.

Comorbid Disease Conditions Associated With CIPN

Comorbid disease conditions prevalent at the time of cancer diagnosis are rarely collected as part of baseline trial data. Therefore, to identify noncancer baseline disease conditions, we linked the SWOG clinical records to Medicare claims data according to Social Security number, sex, and date of birth. We required that patients had at least 6 months of continuous Medicare Parts A and B coverage before study registration to ensure a sufficient minimum amount of coverage to identify potential baseline comorbid conditions. Also, because health maintenance organization providers do not submit claims records to Centers for Medicare & Medicaid Services, patients must simultaneously have had no health maintenance organization coverage. Medicare records were used to identify disease conditions on the basis of Part B, hospital outpatient, and hospital inpatient claims. Events were determined using the International Classification of Diseases (9th revision, clinical modification) diagnosis codes. Only patients who were ≥ 65 years of age at 6 months before enrollment were included.
A comorbid disease condition was identified as any hospital claim—or two or more physician or outpatient claims at least 30 days apart—for diabetes, liver disease, hypothyroidism, hypercholesterolemia, hypertension, varicella zoster, kidney disease, peripheral vascular disease, and autoimmune disease (Appendix Table A2, online only). These conditions are known to be associated with the development of peripheral neuropathy.12

Statistical Methods

Multivariate logistic regression was used to model the odds of experiencing clinically meaningful (grade 2 or greater) neuropathy. Separate models were conducted to examine moderate or worse neuropathy (grades 2 to 4) and severe or worse neuropathy (grades 3 to 4). Only one patient in this study population reported grade 4 neuropathy; therefore, grade 4 neuropathy was not examined as a separate outcome. Each predictor was analyzed in a separate model, and all odds ratios and P values were adjusted for age, race, sex, prognostic risk, date of initial enrollment, and planned treatment time according to the protocol. Additionally, because of heterogeneity due to separate studies, all analyses were stratified by treatment type as defined in the study protocol (docetaxel v paclitaxel) and the inclusion of platinum treatment as part of the treatment course. To assess whether patients with diabetes may have been already predisposed toward clinical neuropathy, we examined the neuropathy rates in a control set of patients from treatment arms for the studies included in this analysis who received no taxane or platinum treatment. P values with alpha < .05 were reported as statistically significant, with no adjustments for multiple comparisons.

Results

Twenty-three studies were included in the analysis (Table 1): nine studies were in lung cancer, five were in genitourinary cancer, four were in breast cancer, three were in head and neck cancer, and two were in gynecologic cancer. Fifteen of the studies were phase II, and eight were phase III. We identified 2,573 patients from these trials age 65 years or older. After restricting to patients with ≥ 6 months of continuous Medicare baseline data, 1,401 patients (55%) were included in the analysis. The number of patients per study ranged from 11 to 408. Fifteen studies comprising 68% of total patients had protocol eligibility criteria, excluding patients with preexisting neuropathy.
Table 1. Studies Included in Analysis
Study No. Cancer Site Cancer Stage Treatment Phase Enrollment
Years Prior Neuropathy Exclusion Level No.
S9712 Lung Poor-risk stage III NSCLC Concurrent carboplatin+VP-16 and radiation followed by paclitaxel II 1999-2000 None 11
S9900 Lung Clinical stages IB-IIIA NSCLC Surgery alone or surgery plus preoperative paclitaxel plus carboplatin III 2000-2004 Grade ≥ 1 38
S9902 H&N Metastatic/recurrent squamous cell carcinoma Docetaxel plus carboplatin II 2000 Grade ≥ 2 12
S9912 GYN Optimally debulked stage II epithelial ovarian, primary peritoneal, or fallopian tube cancer Intravenous paclitaxel, intraperitoneal cisplatin, intravenous liposomal doxorubicin, and intraperitoneal paclitaxel II 1999-2005 Grade ≥ 2 13
S9914 Lung Extensive small-cell lung cancer Paclitaxel, carboplatin, and topotecan with G-CSF II 1999-2001 Grade ≥ 1 21
S9916 GU Advanced, hormone refractory prostate cancer Docetaxel and estramustine v mitoxantrone and prednisone III 2000-2003 None 188
S0003 Lung Advanced NSCLC Cisplatin, paclitaxel, tirapazamine v cisplatin, paclitaxel III 2001-2002 Grade ≥ 2 101
S0007 H&N Advanced/recurrent squamous cell carcinoma Paclitaxel plus cisplatin and fluorouracil II 2001-2003 Grade ≥ 2 16
S0009 GYN Stage III and IV epithelial ovarian cancer, fallopian tube cancer, or primary peritoneal cancer Neoadjuvant paclitaxel plus carboplatin v IV plus IP paclitaxel plus carboplatin II 2002-2005 Grade ≥ 2 20
S0012 Breast Inflammatory and locally advanced breast cancer Standard doxorubicin and cyclophosphamide followed by weekly paclitaxel v weekly doxorubicin and daily oral cyclophosphamide plus G-CSF followed by weekly paclitaxel III 2001-2005 None 23
S0022 Lung Stage IIIB NSCLC Concurrent cisplatin plus docetaxel and radiotherapy followed by consolidation docetaxel II 2001-2002 Grade ≥ 1 12
S0023 Lung Inoperable locally advanced stage III NSCLC Cisplatin plus etoposide plus radiotherapy with consolidation docetaxel followed by maintenance therapy with ZA1839 or placebo III 2002-2005 Grade ≥ 1 89
S0027 Lung Advanced NSCLC in patients ≥ 70 years Sequential vinorelbine and docetaxel II 2001-2003 Grade ≥ 2 69
S0028 GU Metastatic urothelial cancer in patients ≥ 70 years Gemcitabine and paclitaxel II 2001-2006 None 44
S0029 Breast Metastatic breast cancer in patients ≥ 70 years Single-agent docetaxel II 2002-2005 None 12
S0032 GU High-risk metastatic adenocarcinoma Early oral estramustine, oral etoposide, and intravenous paclitaxel in combination with hormone therapy II 2002-2005 None 11
S0102 Breast HER-2 negative, stage IV Docetaxel and vinorelbine plus filgrastim II 2001-2003 Grade ≥ 2 13
S0219 GU Nonmetastatic carcinoma of the bladder Neoadjuvant gemcitabine, paclitaxel, and carboplatin with molecular correlates II 2003-2006 None 31
S0221 Breast Node-positive or high-risk node negative Continuous schedule AC+G v 2-week schedule AC, followed by paclitaxel administered either every 2 weeks or weekly for 12 weeks III 2003-2011 None 127
S0329 H&N Recurrent/metastatic squamous cell carcinoma Gemcitabine and paclitaxel combination administered every 2 weeks II 2005-2006 Grade ≥ 2 23
S0421 GU Advanced hormone refractory prostate cancer Docetaxel and atrasentan v docetaxel and placebo III 2006-2010 Grade ≥ 2 408
S0536 Lung Advanced NSCLC Combination carboplatin, paclitaxel, cetuximab and bevacizumab followed by cetuximab and bevacizumab II 2006-2007 Grade ≥ 2 33
S0819 Lung Advanced NSCLC Carboplatin plus paclitaxel or carboplatin plus paclitaxel plus bevacizumab with or without concurrent cetuximab III 2009-2011 Grade ≥ 2 86
Abbreviations: AC, adriamycin and cytoxan; G; G-CSF; G-CSF, granulocyte colony-stimulating factor; GU, genitourinary; GYN, gynecologic; H&N, head and neck; IV+IP, intravenous and intraperitoneal; NSCLC, non–small-cell lung cancer; VP-16, etoposide.

Patient Characteristics

Patients with a linkage to Medicare claims data were more likely to be non-Hispanic and male, have registered earlier in the period, have received docetaxel, have prostate cancer, have low-risk cancers, and not have received platinum therapy (Table 2). Among Medicare-linked patients, the median age was 72 years (range, 65.5 to 92 years). Although 9% of patients were black, roughly in line with cancer population rates, only 2% were Hispanic. The majority of patients were male (72%), due in part to the predominance of patients with prostate cancer (46%). The median observed time on treatment (108 days) was 14% less than the median planned time on treatment (126 days). The most common comorbid disease conditions were hypertension (68%), hypercholesterolemia (48%), and diabetes (26%).
Table 2. Patient Characteristics
Characteristic Medicare-Linked Patients (N = 1,401) Patients Without Medicare Link (n = 1,172) P* Characteristic Medicare-Linked Patients (N = 1,401)
No. or Median % or Range No. or Median % or Range No. or Median %
Demographic and treatment factors           Baseline comorbid diseases    
Age, years (median or range) 72 65-92 72 65-89 .65  Diabetes with chronic complications 110 8
 Race         .08  Diabetes with or without chronic complications 368 26
 Asian 22 2% 18 2%    Hypothyroidism 231 16
 Black 129 9% 74 6%    Peripheral vascular disease 130 9
 Native 7 < 1% 3 < 1%    Autoimmune diseases* 79 6
 Unknown 20 1% 18 2%    Sjögren’s syndrome 12 < 1
 White 1,223 87% 1,059 90%    Lupus 2 < 1
Ethnicity         .05  Rheumatoid arthritis 49 3
 Not Hispanic 1,371 98% 1,132 97%    Scleroderma 27 2
 Hispanic 30 2% 40 3%    Mixed connective tissue disease 0
Sex         .01  Dermatomyositis 0
 Female 388 28% 377 32%    Polymyositis 0
 Male 1,013 72% 795 68%    Vasculitis 0
Time of initial registration         < .001  Giant cell arteritis 0
 < 2004 588 42% 294 25%    HIV 0
 2004 or later 813 58% 878 75%    Varicella zoster 37 3
Kind of taxane         < .001  Hypertension 956 68
 Docetaxel 803 57% 486 41%    Hypercholesterolemia 673 48
 Paclitaxel 598 43% 686 59%        
Planned time receiving treatment according to protocol, days (median or range) 126 42-252 126 42-252 .002      
Observed time on treatment, days (median or range) 108 1-1,776 105 1-864 .01      
Type of cancer         < .001      
 Bladder 31 2% 15 1%        
 Breast 175 12% 116 10%        
 Head & neck 51 4% 9 1%        
 Lung 460 33% 639 55%        
 Ovarian 33 2% 6 1%        
 Prostate 651 46% 387 33%        
Cancer stage/high risk         .001      
 Low 781 56% 577 49%        
 High 620 44% 594 51%        
Total time of Medicare coverage prior to registration, years (median or range) 3.7 0.5-13        
Platinum therapy as part of protocol 483 34% 645 55% < .001      
Total time of Medicare coverage prior to registration, years (median or range) 3.7 0.5-13        
*
P value uses t tests for continuous variables and χ2 tests for categorical variables to compare those patients linked to Medicare claims data with those patients not linked to Medicare claims data.

Predictors of Neuropathy

In total, 251 of 1,401 patients (18%) had grade 2 or worse neuropathy, and 121 (9%) had grade 3 or worse neuropathy. (For comparison, among patients who were younger than 65 years in these trials and not included in this analysis, the rate of grade 2 to 4 CIPN was 15%, and the rate of grade 3 to 4 CIPN was 9%.) Demographic, clinical, and treatment predictors of neuropathy are listed in Table 3. Patients who received paclitaxel were more likely to experience grade 2 to 4 neuropathy (25% v 12%; OR, 2.20; 95% CI, 1.52 to 3.18; P < .001) and grade 3 to 4 neuropathy (13% v 5%; OR, 2.86; 95% CI, 1.70 to 4.80; P < .001) than were those who received docetaxel. Patients who received platinum treatment with a taxane were more likely to experience grade 2 to 4 neuropathy (26% v 14%; OR, 1.68; 95% CI, 1.18 to 2.40; P = .004) than were those who did not. For each increase in age of 1 year, the odds of neuropathy increased by 4% (P = .006).
Table 3. Neuropathy Rates According to Demographic, Clinical, and Treatment Characteristics
Characteristic Grades 2-4 Neuropathy Grades 3-4 Neuropathy
No, No. (%) Yes, No. (%) OR (95% CI)* P* No, No. (%) Yes, No. (%) OR (95% CI)* P*
Total 1,150 (82) 251 (18)     1,280 (91) 121 (9)    
Mean age (years) 72.5 73.0 1.04 (1.01 to 1.07) .006 72.6 73.1 1.04 (1.00 to 1.08) .03
Age, categories (years)                
 < 75 806 (82) 172 (18) Reference   898 (92) 80 (8) Reference  
 ≥ 75 344 (81) 79 (19) 1.28 (0.94 to 1.75) .12 382 (90) 41 (10) 1.46 (0.97 to 2.22) .07
Race                
 Asian/Pacific Islander 16 (73) 6 (27) 2.00 (0.75 to 5.29) .16 17 (77) 5 (23) 3.63 (1.26 to 10.50) .02
 Black 112 (87) 17 (13) 0.84 (0.49 to 1.44) .52 121 (94) 8 (6) 0.86 (0.41 to 1.84) .70
 Native 7 (100) 0     7 (100) 0    
 Unknown 16 (80) 4 (20) 0.99 (0.32 to 3.07) .99 18 (90) 2 (10) 1.16 (0.26 to 5.16) .85
 White 999 (82) 224 (18) Reference   1,117 (91) 106 (9) Reference  
Ethnicity                
 Not Hispanic 1,123 (82) 248 (18) Reference   1,252 (91) 119 (9) Reference  
 Hispanic 27 (90) 3 (10) 0.46 (0.13 to 1.61) .23 28 (93) 2 (7) 0.61 (0.13 to 2.75) .52
Sex                
 Female 311 (80) 77 (20) Reference   343 (88) 45 (12) Reference  
 Male 839 (83) 174 (17) 1.06 (0.74 to 1.50) .76 937 (92) 76 (8) 0.82 (0.52 to 1.29) .39
Time of initial registration                
 < 2004 475 (81) 113 (19) Reference   526 (89) 62 (11) Reference  
 2004 or later 675 (83) 138 (17) 0.97 (0.72 to 1.31) .87 754 (93) 59 (7) 0.63 (0.42 to 0.94) .02
Kind of taxane                
 Docetaxel 704 (88) 99 (12) Reference   761 (95) 42 (5) Reference  
 Paclitaxel 446 (75) 152 (25) 2.20 (1.52 to 3.18) < .001 519 (87) 79 (13) 2.86 (1.70 to 4.80) < .001
Cancer stage/high risk                
 Low 643 (82) 138 (18) Reference   713 (91) 68 (9) Reference  
 High 507 (82) 113 (18) 1.00 (0.75 to 1.33) 1.00 567 (91) 53 (9) 0.89 (0.60 to 1.32) .56
Planned treatment time in protocol, days                
 < 126 389 (83) 82 (17) Reference   430 (91) 41 (9) Reference  
 ≥ 126 761 (82) 169 (18) 1.05 (0.71 to 1.55) .79 850 (91) 80 (9) 1.34 (0.81 to 2.22) .26
Platinum treatment                
 No 793 (86) 125 (14) Reference   855 (93) 63 (7) Reference  
 Yes 357 (74) 126 (26) 1.68 (1.18 to 2.40) .004 425 (88) 58 (12) 1.08 (0.67 to 1.74) .77
*
Odds ratios and P values adjusted for age, race (black/white/other), sex, cancer stage/risk, date of initial enrollment, and planned treatment time according to the protocol (at or above v below the median), and stratified by treatment type (docetaxel v paclitaxel) and platinum treatment (yes/no).
Compared with patients without diabetes, grade 2 to 4 neuropathy was observed more often in patients with diabetes with complications (16% v 25%, respectively) and in patients with diabetes with or without complications (16% v 22%, respectively; Fig 1A; Appendix Table A3, online only). In contrast, patients with autoimmune disease were less likely to have grade 2 to 4 neuropathy compared with those without autoimmune disease (11% v 18%, respectively). Similarly, grade 3 to 4 neuropathy was most common in patients with diabetes with complications (8% v 12% respectively) and least common in patients with autoimmune disease (9% v 4%, respectively; Fig 1B).
Fig 1. Grade 2 to 4 (A) and grade 3 to 4 (B) neuropathy rates by comorbid disease category. Each bar represents the proportion with neuropathy for patients with the specified condition (blue) or without the specified condition (gold). The P values shown above each set of bars show the statistical significance for the covariate representing whether a patient had the specified condition (ie, with v without condition) from the multivariable logistic regression analyses. The comorbid disease categories are sorted in descending order of the odds ratio for having grade 2 to 4 neuropathy, derived from multivariable regression analyses. P values were derived from multivariable logistic regression models adjusting for age, race (black/white/other), sex, cancer stage/risk, date of initial enrollment, and planned treatment time according to the protocol (at or above v below the median), and stratified by treatment type (docetaxel v paclitaxel) and platinum treatment (yes/no). For the analysis of diabetes with chronic complications, the comparison is between patients with diabetes plus complications versus patients with no diabetes. Patients with diabetes without complications are excluded from this analysis. Autoimmune diseases include Sjögren’s syndrome, lupus, rheumatoid arthritis, scleroderma, mixed connective tissue disease, dermatomyositis, polymyositis, vasculitis, and giant cell arteritis. VD, vascular disease.
In a multivariable logistic regression model controlling for clinical and demographic factors (Fig 2), patients with diabetic complications had twice the odds of having grade 2 to 4 neuropathy (OR, 2.13; 95% CI, 1.31 to 3.46; P = .002) compared with those without. Similarly, patients with diabetes with or without complications had two thirds greater odds of having neuropathy (OR, 1.67; 95% CI, 1.23 to 2.27; P = .001). In contrast, patients with autoimmune disease were half as likely to experience grade 2 to 4 neuropathy (OR, 0.49; 95% CI, 0.24 to 1.02; P = .06) and one third as likely to experience grade 3 to 4 neuropathy (OR, 0.32; 95% CI, 0.10 to 1.03; P = .06) compared with those without autoimmune disease. There was no evidence that the other disease conditions associated with neuropathy were associated with neuropathy in this set of studies.
Fig 2. Forest plot of the association of neuropathy grade with each comorbid condition, controlling for demographic, clinical, and treatment characteristics. Each box represents the odds ratio, and each line represents the 95% CI around the estimated odds ratio. The vertical line shows the line of equal odds. Odds ratios to the right of the vertical line indicate that patients with the specified condition had higher odds of grade 2 to 4 or grade 3 to 4 neuropathy, and odds ratios to the left of the vertical line indicate that patients with the specified condition had lower odds of grade 2 to 4 or grade 3 to 4 neuropathy. The comorbid disease categories are sorted in descending order of the odds ratio for having grade 2 to 4 neuropathy in multivariable regression. Odds ratios and P values were derived from multivariable logistic regression models, adjusting for age, race (black/white/other), sex, cancer stage and risk, date of initial enrollment, and planned treatment time according to the protocol (at or above v below the median), and stratified by treatment type (docetaxel v paclitaxel) and platinum treatment (yes/no). For the analysis of diabetes with chronic complications, the comparison is between patients with diabetes plus complications versus patients with no diabetes. Patients with diabetes without complications were excluded from this analysis. Autoimmune diseases include Sjögren’s syndrome, lupus, rheumatoid arthritis, scleroderma, mixed connective tissue disease, dermatomyositis, polymyositis, vasculitis, and giant cell arteritis. Each square represents an odds ratio, and each horizontal line is the 95% CI. The vertical line is the line of equal odds.

CIPN Rates in Non–Taxane-Treated Patients

Among the 23 studies included in the analysis, two phase III trials (S9900 and S9916) included treatment arms with no taxane or platinum treatment, comprising 227 control patients (Appendix Table A4, online only). Among these, 12 had diabetes with complications, 47 had diabetes with or without complications, and five had an autoimmune disease. None of these control patients with these baseline conditions reported neuropathy while in the study. In patients with diabetes, with or without complications, there were much higher rates of grade 2 to 4 neuropathy (22% v 0%; P < .001) and grade 3 to 4 neuropathy (11% v 0%; P = .02) among those on taxane therapy. Results were similar but less extreme (likely due to smaller samples) for patients who had diabetes with complications (25% v 0%, P = .05, and 12% v 0%, P = .21, respectively) and for patients with an autoimmune disease (11% v 0%, P = .42, and 4% v 0%, P = .66, respectively). These findings are consistent with the hypothesis that it was the use of taxane therapy in patients with diabetes or autoimmune diseases, rather than the disease conditions themselves, that resulted in different CIPN rates.

Sensitivity Analyses

In sensitivity analysis, we considered a longer, 1-year prestudy window for continuous Medicare coverage to identify comorbid conditions. Results were similar (data not shown). There were also no substantive changes to the results when planned treatment time was considered as a continuous variable (data not shown). In the subset of studies that excluded patients with preexisting neuropathy, patients with autoimmune disease were less likely to have grade 2 to 4 or 3 to 4 neuropathy, but the strength of the association was diminished. Finally, with diabetes included as a baseline covariate, the association of autoimmune status and grade 2 to 4 and grade 3 to 4 neuropathy was statistically significant (P = .04). Minimal other changes were evident when diabetes and autoimmune disease were included as covariates.

Discussion

Using a novel linkage between a large cohort of elderly patients enrolled in SWOG clinical trials and Medicare claims, we found that patients with a baseline history of diabetes and, in particular, those with a history of complications from diabetes, have a substantially higher risk of developing CIPN. We also observed that patients with autoimmune disease may have a lower risk of developing CIPN. In addition, compared with docetaxel, patients receiving paclitaxel had more than double the risk, and those who had the addition of a platinum agent had more than two thirds increased odds of developing CIPN.
Diabetic peripheral neuropathy is the most common complication in patients with diabetes and the most common cause of neuropathy worldwide.13 Early metabolic abnormalities in the nerves are thought to be due to the direct exposure of nerve tissue or its vascular bed to high concentrations of glucose.14 The presence and severity increases over time with poor glycemic control. Much of the prior research evaluating the association between diabetes and CIPN has come from retrospective trials in which it is difficult to determine what component of the neuropathy is from the diabetes and what is from the exposure.10,11,15 To estimate the association of diabetes with CIPN, investigators evaluated the development of hyperglycemia as a surrogate for diabetes. They found that patients who developed hyperglycemia while receiving taxane therapy had an odds ratio of 1.47 for developing grade 2 to 4 CIPN.8 Prospective trials that include agents that are known to cause CIPN typically exclude patients with severe neuropathy; in this study, more than two thirds of patients were from trials that excluded patients with preexisting neuropathy. Furthermore, we found no neuropathy in a control set of patients who received no taxane therapy. Thus, we feel confident that the neuropathy observed in patients with diabetes developed while receiving taxane therapy.
In addition to diabetes, peripheral neuropathy is caused by a number of other diseases and disorders. Underproduction of thyroid hormone can slow metabolism and lead to fluid accumulation, which can exert pressure on peripheral nerves.12 Vasculitis can impair blood flow to nerves, which decreases oxygen supply to the peripheral nerves, resulting in subsequent nerve damage.12 Infections such as herpes varicella zoster and HIV can damage sensory nerves. In addition, medications that are commonly used to treat hypertension and high cholesterol can also result in peripheral neuropathy. We did not see an increased risk of CIPN among patients who had a history of these conditions.
Other than age, we did not find other demographic factors such as gender, ethnicity, or self-reported race to be associated with the development of CIPN. Our sample only included patients age 65 years and older who received Medicare. Other studies evaluating the association between age and CIPN have reported conflicting results; however, the mean age in those studies was significantly younger than our cohort.8,15,16 The association between black race and the development of CIPN has also been inconsistent. An analysis of patients with early-stage breast cancer did not show an association between self-reported black race and CIPN; however, a genome-wide association study of patients in the same study found an association between genetically determined African ancestry and taxane-induced CIPN.7 Similarly, in an analysis from a SWOG adjuvant breast cancer trial, an African American–specific haplotype was associated with an almost threefold increase in risk of CIPN.17 These studies did not have information on baseline diabetes. Because racial minorities have higher prevalence rates of diabetes, worse diabetes control, and higher rates of diabetes-associated complications, it has been difficult to ascertain an independent effect of black race.18 The current analysis provides a detailed assessment of the risk associated with diabetes.
We were intrigued by the borderline, significant, protective effect of a history of autoimmune disease with the development of CIPN. Sjögren’s syndrome, rheumatoid arthritis, and lupus can result in autoantibodies that directly cause nerve damage.19 Although the mechanism contributing to the development of CIPN is poorly understood, there may be a relationship among the immune system, inflammation, and peripheral neuropathy.20,21 If so, it is possible that prior anti-inflammatory treatment may have been protective against the development of CIPN in these patients. It has been hypothesized that inflammatory cascade activation, proinflammatory cytokine upregulation, and neuroimmune communication pathways may play essential roles in the initiation and progression of CIPN.22 Paclitaxel-induced CIPN was found to be associated with the activation of microglia following the expression and release of proinflammatory cytokines in the spinal dorsal horn.23 If these pathways are already active in patients with autoimmune disease, chemotherapy may have a less dramatic effect.
We acknowledge several limitations of our study and of the Medicare database in general. All the patients were older than 65 years of age, and elderly patients are often not accrued to clinical trials. Patients were also required to have 6 or more months of continuous Medicare claims before study registration. This may influence the generalizability of the findings. Although we required patients to have two claims to reduce misclassification bias, a process routinely performed in seeking diagnoses, it is still possible that not all patients with Medicare claims had the comorbid condition we assigned.24-26 Other factors known to be associated with neuropathy, such as medication, obesity, and history of alcohol use, were not available. Also, some comorbid conditions were rare; therefore, power to identify their relationship with neuropathy was limited. It is possible that our results are not generalizable to younger patients. All the patients were enrolled in a clinical trial; therefore, these results may not be generalizable to all patients who did not meet eligibility criteria for one of the SWOG trials, because the majority of patients had a performance status of 0 or 1 and did not have end-organ damage or any medical condition that was uncontrolled at the time of enrollment. Finally, our goal was to identify potential predictors of neuropathy for future examination; therefore, no adjustments for multiple comparisons were made. However, in some instances (eg, taxane type, diabetes), the strength of the association between the predictor and neuropathy would have remained statistically significant, even under conservative multiple comparisons approaches.
In summary, we have shown that in addition to drug-related factors and duration of therapy, age and history of diabetes are independent predictors of the development of CIPN. Interestingly, we also found a suggestion that a prior history of an autoimmune disease was associated with lower rates of neuropathy. Future studies should be performed to understand the role of the immune system and cytokine activation in the development and prevention of CIPN. In the meantime, patients with diabetic complications should consider avoiding paclitaxel or taxane plus platinum combination therapies, if other options exist.
Listen to the podcast by Dr Paice at www.jco.org/podcasts
D.L.H. (NCI R01CA134964) and J.D.W. (NCI R01CA169121-01A1) are recipients of grants from the National Cancer Institute, Division of Cancer Prevention, National Cancer Institute Community Oncology Research Program Research Base Grant No. 1UG1CA189974-01. D.L.H. is the recipient of a grant from the American Society of Clinical Oncology and the Breast Cancer Research Foundation.

Authors' Disclosures of Potential Conflicts of Interest

Comorbidities and Risk of Chemotherapy-Induced Peripheral Neuropathy Among Participants 65 Years or Older in Southwest Oncology Group Clinical Trials

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or jco.ascopubs.org/site/ifc.

Dawn L. Hershman

No relationship to disclose

Cathee Till

No relationship to disclose

Jason D. Wright

Research Funding: Genentech (Inst)

Danielle Awad

No relationship to disclose

Scott D. Ramsey

No relationship to disclose

William E. Barlow

No relationship to disclose

Lori M. Minasian

No relationship to disclose

Joseph Unger

No relationship to disclose

References

1.
DL Hershman, LH Weimer, A Wang, etal: Association between patient reported outcomes and quantitative sensory tests for measuring long-term neurotoxicity in breast cancer survivors treated with adjuvant paclitaxel chemotherapy Breast Cancer Res Treat 125:767–774,2011
2.
JJ Lee, SM Swain: Peripheral neuropathy induced by microtubule-stabilizing agents J Clin Oncol 24:1633–1642,2006
3.
BP Schneider, DL Hershman, C Loprinzi: Symptoms: Chemotherapy-induced peripheral neuropathy Adv Exp Med Biol 862:77–87,2015
4.
DL Hershman, C Lacchetti, RH Dworkin, etal: Prevention and management of chemotherapy-induced peripheral neuropathy in survivors of adult cancers: American Society of Clinical Oncology clinical practice guideline J Clin Oncol 32:1941–1967,2014
5.
EK Rowinsky, V Chaudhry, AA Forastiere, etal: Phase I and pharmacologic study of paclitaxel and cisplatin with granulocyte colony-stimulating factor: Neuromuscular toxicity is dose-limiting J Clin Oncol 11:2010–2020,1993
6.
EK Rowinsky, EA Eisenhauer, V Chaudhry, etal: Clinical toxicities encountered with paclitaxel (Taxol) Semin Oncol 20:1–15,1993 suppl 3
7.
BP Schneider, L Li, M Radovich, etal: Genome-wide association studies for taxane-induced peripheral neuropathy in ECOG-5103 and ECOG-1199 Clin Cancer Res 21:5082–5091,2015
8.
BP Schneider, F Zhao, M Wang, etal: Neuropathy is not associated with clinical outcomes in patients receiving adjuvant taxane-containing therapy for operable breast cancer J Clin Oncol 30:3051–3057,2012
9.
H Gogas, F Shapiro, C Aghajanian, etal: The impact of diabetes mellitus on the toxicity of therapy for advanced ovarian cancer Gynecol Oncol 61:22–26,1996
10.
Kus T, Aktas G, Kalender ME, et al: Taxane-induced peripheral sensorial neuropathy in cancer patients is associated with duration of diabetes mellitus: A single-center retrospective study. Support Care Cancer 24:1175-1179, 2016
11.
P de la Morena Barrio, MA Conesa, E González-Billalabeitia, etal: Delayed recovery and increased severity of paclitaxel-induced peripheral neuropathy in patients with diabetes J Natl Compr Canc Netw 13:417–423,2015
12.
National Institute of Neurological Disorders and Stroke: Peripheral neuropathy fact sheet. http://www.ninds.nih.gov/disorders/peripheralneuropathy/detail_peripheralneuropathy.htm
13.
G Said: Diabetic neuropathy: A review Nat Clin Pract Neurol 3:331–340,2007
14.
J Partanen, L Niskanen, J Lehtinen, etal: Natural history of peripheral neuropathy in patients with non-insulin-dependent diabetes mellitus N Engl J Med 333:89–94,1995
15.
Y Kanbayashi, T Hosokawa, J Kitawaki, etal: Statistical identification of predictors for paclitaxel-induced peripheral neuropathy in patients with breast or gynaecological cancer Anticancer Res 33:1153–1156,2013
16.
Pereira S, Fontes F, Sonin T, et al: Chemotherapy-induced peripheral neuropathy after neoadjuvant or adjuvant treatment of breast cancer: A prospective cohort study. Support Care Cancer 24:1571-1581, 2016
17.
LE Sucheston, H Zhao, S Yao, etal: Genetic predictors of taxane-induced neurotoxicity in a SWOG phase III intergroup adjuvant breast cancer treatment trial (S0221) Breast Cancer Res Treat 130:993–1002,2011
18.
ME Peek, A Cargill, ES Huang: Diabetes health disparities: A systematic review of health care interventions Med Care Res Rev 64:101S–156S,2007 5 suppl
19.
S Bhattacharyya, SM Helfgott: Neurologic complications of systemic lupus erythematosus, Sjögren syndrome, and rheumatoid arthritis Semin Neurol 34:425–436,2014
20.
AC Stork, WL van der Pol, H Franssen, etal: Clinical phenotype of patients with neuropathy associated with monoclonal gammopathy: A comparative study and a review of the literature J Neurol 261:1398–1404,2014
21.
AC Stork, BC Jacobs, AP Tio-Gillen, etal: Prevalence, specificity and functionality of anti-ganglioside antibodies in neuropathy associated with IgM monoclonal gammopathy J Neuroimmunol 268:89–94,2014
22.
XM Wang, TJ Lehky, JM Brell, etal: Discovering cytokines as targets for chemotherapy-induced painful peripheral neuropathy Cytokine 59:3–9,2012
23.
M Naguib, JJ Xu, P Diaz, etal: Prevention of paclitaxel-induced neuropathy through activation of the central cannabinoid type 2 receptor system Anesth Analg 114:1104–1120,2012
24.
GL Smith, BD Smith, TA Buchholz, etal: Cerebrovascular disease risk in older head and neck cancer patients after radiotherapy J Clin Oncol 26:5119–5125,2008
25.
SH Giordano, A Lee, YF Kuo, etal: Late gastrointestinal toxicity after radiation for prostate cancer Cancer 107:423–432,2006
26.
MJ Hassett, AJ O’Malley, JR Pakes, etal: Frequency and cost of chemotherapy-related serious adverse effects in a population sample of women with breast cancer J Natl Cancer Inst 98:1108–1117,2006

Appendix

Table A1. Definitions of Adverse Risk Levels for Construction of Prognostic Risk Score
Study No. Cancer Site Study-Specific Prognostic Factors Adverse (ie, Poor Prognosis) Risk Levels No. of Risk Factors to Be Considered High Risk
S9712 Lung Weight loss (< 5% v ≥ 5%) Weight loss ≥ 5% ≥ 2
T stage (T1/T2 v T3/T4) T stage T3/T4
N stage (N0/N1 v N2/N3) N stage N2/N3
LDH (≤ IULN v > IULN) LDH>IULN
S9900 Lung Clinical stage (IB/IIA v IIB/IIA) Clinical stage IIB/IIIA 1
S9902 H&N Disease type (metastatic v nonmetastatic) Metastatic disease 1
S9912 GYN Stage (IIIA/IIIB v IIIC/IV) Stage IIIC/IV 1
S9914 Lung Weight loss (< 5% v ≥ 5%) Weight loss ≥ 5% ≥ 1
LDH (≤ IULN v > IULN) LDH > IULN
S9916 GU Type of progression (PSA only v measurable/evaluable) Measurable/evaluable disease ≥ 2
Bone pain (grade < 2 v ≥ 2) Bone pain grade ≥ 2
Performance status (0/1 v 2/3) Performance status 2-3
S0003 Lung Weight loss (< 5% v ≥ 5%) Weight loss ≥ 5% ≥ 2
Stage (IIIB v IV) Stage IV
LDH (≤ IULN v > IULN) LDH > IULN
S0007 H&N Performance status (0/1 v 2) Performance status 2 ≥ 1
Disease type (nonmetastatic v metastatic) Metastatic disease
S0009 GYN Stage (III v IV) Stage IV ≥ 1
Performance status (0/1 v 2) Performance status 2
S0012 Breast Inflammatory disease (no v yes) Inflammatory disease, yes 1
S0022 Lung Weight loss (< 5% v ≥ 5%) Weight loss ≥ 5% ≥ 2
T stage (T1/T2/T3 v T4) T stage T4
N stage (N0/N1/N2 v N3) N stage N3
LDH (≤ IULN v > IULN) LDH > IULN
S0023 Lung T stage (T1/T2 v T3/T4) T stage T3/T4 ≥ 2
N stage (N0/N1 v N2/N3) N stage N2/N3
Histologic/cytologic subtype (nonsquamous v squamous) Squamous histologic/cytologic subtype
S0027 Lung Age (< 70 v ≥ 70) Age ≥ 70 2
Performance status (0/1 v 2) Performance status 2
S0028 GU Age (< 60 v ≥ 70) Age ≥ 70 1
S0029 Breast Age (< 60 v ≥ 70) Age ≥ 70 1
S0032 GU Bone metastases (no v yes) Bone metastases, yes 2
Bone pain (< 2 v ≥ 2) Bone pain ≥ 2
S0102 Breast ER/PR status (either or both positive or borderline or unknown v both negative) ER/PR status both negative 1
S0219 GU T stage (T2 v T3/T4a) T stage T3/T4a ≥ 1
Performance status (0-1 v 2) Performance status 2
S0221 Breast Nodal status (0-3 v ≥ 4) Nodal status ≥ 4 nodes ≥ 2
HER2, ER, PR status HER2– and ER and/or PR+: score = 0
(negative v positive) HER2+ and ER and PR either – or +: score = 1
  HER2– and ER− and PR−: score = 2
S0329 H&N Disease type (nonmetastatic v metastatic) Metastatic disease 1
S0421 GU Type of progression (PSA only v measurable/evaluable) Measurable/evaluable disease ≥ 3
Prior use of bisphosphonates (no v yes) Prior use of bisphosphonates, yes
Worst pain (< 4 v ≥ 4) Worst pain ≥ 4
Extraskeletal metastases (no v yes) Extraskeletal metastases, yes
S0536 Lung Stage (IIIB v IV) Stage IV 2
Smoking history (former/never v current) Current smoker
S0819 Lung Bevacizumab status (appropriate v inappropriate) Bevacizumab, inappropriate ≥ 2
Smoking history (former/never v current) Current smoker
M stage (M1a v M1b) M stage M1b
Abbreviations: ER, estrogen receptor; GU, genitourinary; GYN, gynecologic; HER2, human epidermal growth factor receptor 2; H&N, head and neck; IULN, institutional upper limit of normal; LDH, lactate dehydrogenase; PR, progesterone receptor; PSA, prostate-specific antigen.
Table A2. Codes for Comorbid Conditions
Comorbid Condition ICD9 Code
Diabetes with chronic complications 250.40, 250.41, 250.42, 250.43, 250.50, 250.51, 250.52, 250.53, 250.60, 250.61, 250.62, 250.63, 250.70, 250.71, 250.72, 250.73, 250.90, 250.91, 250.92, 250.93
Diabetes with or without chronic complications 249.00, 249.01, 250.00, 250.01, 250.02, 250.03, 250.10, 250.11, 250.12, 250.13, 250.20, 250.21, 250.22, 250.23, 250.30, 250.31, 250.32, 250.33, 250.80, 250.81, 250.82, 250.83, 250.90, 250.91, 250.92, 250.93, 250.40, 250.41, 250.42, 250.43, 250.50, 250.51, 250.52, 250.53, 250.60, 250.61, 250.62, 250.63, 250.70, 250.71, 250.72, 250.73, 250.90, 250.91, 250.92, 250.93
Hypothyroidism 246.9, 794.5, V77.0, 240.9, 243, 244.0, 244.1, 244.2, 244.3, 244.8, 244.9, 246.1, 246.8
Hypercholesterolemia 272.2, 272.4
Hypertension 401.0, 401.1, 401.9, 402.00, 402.01, 402.10, 402.11, 402.90, 402.91
Varicella zoster 053.0, 053.10, 053.11, 053.14, 053.19, 053.20, 053.21, 053.22, 053.29, 053.71, 053.79, 053.8, 053.9
Peripheral vascular disease 093.0, 437.3, 440.0, 440.1, 440.20, 440.21, 440.22, 440.23, 440.24, 440.29, 440.30, 440.31, 440.32, 440.4, 440.8, 440.9, 441.00, 441.01, 441.02, 441.03, 441.1, 441.2, 441.3, 441.4, 441.5, 441.6, 441.7, 441.9, 443.1, 443.21, 443.22, 443.23, 443.24, 443.29, 443.81, 443.82, 443.89, 443.9, 447.1, 557.1, 557.9, V43.4
Autoimmune diseases  
 Sjögren's syndrome 370.33
 Lupus 373.34, 695.4, 71.0
 Rheumatoid arthritis V82.1, 446.0, 446.1, 446.20, 446.21, 446.29, 446.3, 446.4, 446.5, 446.6, 446.7, 701.0, 710.0, 710.1, 710.2, 710.3, 710.4, 710.8, 710.9, 711.20, 711.21, 711.22, 711.23, 711.24, 711.25, 711.26, 711.27, 711.28, 711.29, 714.0, 714.1, 714.2, 714.30, 714.31, 714.32, 714.33, 714.4, 714.81, 714.89, 714.9, 719.30, 719.31, 719.32, 719.33, 719.34, 719.35, 719.36, 719.37, 719.38, 719.39, 720.0, 720.1, 720.2, 720.81, 720.89, 720.9, 725, 728.5, 728.89, 729.30, 729.31, 729.39
 Scleroderma 701.0, 701.1, 517.2
 Mixed connective tissue disease 710.8
 Dermatomyositis 710.3
 Polymyositis 710.4
 Vasculitis 362.18
 Giant cell arteritis 446.5
 Kidney disease 250.40, 250.41, 250.42, 250.43, 285.21, 403.00, 403.01, 403.10, 403.11, 403.90, 403.91, 404.00, 404.01, 404.02, 404.03, 404.10, 404.11, 404.12, 404.13, 404.90, 404.91, 404.92, 404.93, 580.89, 580.9, 581.89, 581.9, 582.89, 582.9, 583.6, 583.7, 585.1, 585.2, 585.3, 585.4, 585.5, 585.9, 794.4
 Liver disease 571.2, 571.3, 571.5, 571.8, 571.9, 572.8, 573, 573.8, 573.9
Abbreviation: ICD9, International Classification of Diseases (9th revision, clinical modification).
Table A3. Adjusted Association Between Baseline Conditions and Chemotherapy-Induced Peripheral Neuropathy
  Grades 2-4 Neuropathy Grades 3-4 Neuropathy
No, No. (%) Yes, No. (%) OR (95% CI)* P* No, No. (%) Yes, No. (%) OR (95% CI)* P*
  1,150 (82) 251 (18)     1,280 (91) 121 (9)    
Diabetes with chronic complications†                
 No 864 (83.7) 169 (16.3) Reference   952 (92.2) 81 (7.8) Reference  
 Yes 82 (74.5) 28 (25.5) 2.13 (1.31 to 3.46) .002 97 (88.2) 13 (11.8) 1.73 (0.90 to 3.32) .10
Diabetes with or without chronic complications                
 No 864 (83.6) 169 (16.4) Reference   952 (92.2) 81 (7.8) Reference  
 Yes 286 (77.7) 82 (22.3) 1.67 (1.23 to 2.27) .001 328 (89.0) 40 (11.0) 1.61 (1.07 to 2.42) .02
Liver Disease                
 No 1,005 (83) 212 (17) Reference   1,112 (91) 105 (9) Reference  
 Yes 145 (79) 39 (21) 1.27 (0.85 to 1.89) .24 168 (91) 16 (9) 0.98 (0.56 to 1.73) .95
Hypothyroidism                
 No 966 (82.6) 204 (17.4) Reference   1,072 (91.6) 98 (8.4) Reference  
 Yes 184 (79.7) 47 (20.3) 1.12 (0.77 to 1.63) .56 208 (90.0) 23 (10.0) 1.05 (0.64 to 1.74) .84
Hypercholesterolemia                
 No 604 (83.0) 124 (17.0) Reference   671 (92.2) 57 (7.8) Reference  
 Yes 546 (81.1) 127 (18.9) 1.07 (0.80 to 1.43) .66 609 (90.5) 64 (9.5) 1.23 (0.83 to 1.84) .30
Hypertension                
 No 365 (82.0) 80 (18.0) Reference   410 (92.1) 35 (7.9) Reference  
 Yes 785 (82.1) 171 (17.9) 0.97 (0.71 to 1.31) .83 870 (91.0) 86 (9.0) 1.15 (0.75 to 1.77) .51
Varicella zoster                
 No 1,119 (82.0) 245 (18.0) Reference   1,247 (91.4) 117 (8.6) Reference  
 Yes 31 (83.8) 6 (16.2) 0.82 (0.33 to 2.03) .67 33 (89.2) 4 (10.8) 1.18 (0.40 to 3.48) .77
Kidney disease                
 No 979 (81) 224 (19) Reference   1,093 (91) 110 (9) Reference  
 Yes 171 (86) 27 (14) 0.73 (0.46 to 1.14) .16 187 (94) 11 (6) 0.65 (0.34 to 1.25) .19
Peripheral vascular disease                
 No 1,040 (81.8) 231 (18.2) Reference   1,158 (91.1) 113 (8.9) Reference  
 Yes 110 (84.6) 20 (15.4) 0.71 (0.43 to 1.19) .19 122 (93.8) 8 (6.2) 0.62 (0.29 to 1.31) .21
Autoimmune diseases‡                
 No 1,080 (81.7) 242 (18.3) Reference   1,204 (91.1) 118 (8.9) Reference  
 Yes 70 (88.6) 9 (11.4) 0.49 (0.24 to 1.02) .06 76 (96.2) 3 (3.8) 0.32 (0.10 to 1.03) .06
*
Odds ratios and P values adjusted for age, race (black/white/other), sex, cancer stage/risk, date of initial enrollment, and planned treatment time according to the protocol (at or above v below the median), and stratified by treatment type (docetaxel v paclitaxel) and platinum treatment (yes/no).
The comparison is between patients with diabetes plus complications versus patients with no diabetes. Patients with diabetes without complications are excluded from this analysis.
Includes Sjögren’s syndrome, lupus, rheumatoid arthritis, scleroderma, mixed connective tissue disease, dermatomyositis, polymyositis, vasculitis, and giant cell arteritis.
Table A4. CIPN Rates in Taxane- Versus Non–Taxane-Treated Patients
  Grades 2-4 Neuropathy Grade 3-4 Neuropathy
No, No. (%) Yes, No. (%) P* No, No. (%) Yes, No. (%) P*
Diabetes with chronic complications            
 Taxane 82 (75) 28 (25)   97 (88) 13 (12)  
 No taxane 12 (100) 0 (0) .05 12 (6) 0 (0) .21
Diabetes with or without chronic complications            
 Taxane 286 (78) 82 (22)   328 (89) 40 (11)  
 No taxane 47 (100) 0 (0) < .001 47 (100) 0 (0) .02
Autoimmune diseases†            
 Taxane 70 (89) 9 (11)   76 (96) 3 (4)  
 No taxane 5 (100) 0 (0) .42 5 (100) 0 (0) .66
Abbreviation: CIPN, chemotherapy-induced peripheral neuropathy.
*
P value from χ2 test.
Autoimmune diseases include Sjögren’s syndrome, lupus, rheumatoid arthritis, scleroderma, mixed connective tissue disease, dermatomyositis, polymyositis, vasculitis, and giant cell arteritis.

Information & Authors

Information

Published In

Journal of Clinical Oncology
Pages: 3014 - 3022
PubMed: 27325863

History

Published online: June 20, 2016
Published in print: September 01, 2016

Permissions

Request permissions for this article.

Authors

Affiliations

Dawn L. Hershman [email protected]
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
Cathee Till
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
Jason D. Wright
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
Danielle Awad
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
Scott D. Ramsey
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
William E. Barlow
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
Lori M. Minasian
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.
Joseph Unger
Dawn L. Hershman, Jason D. Wright, and Danielle Awad, Columbia University Medical Center, New York, NY; Cathee Till, Scott D. Ramsey, and Joseph Unger, Fred Hutchinson Cancer Research Center; William E. Barlow, University of Washington, Seattle, WA; and Lori M. Minasian, National Cancer Institute, Bethesda, MD.

Notes

Corresponding author: Dawn L. Hershman, MD, MS, Columbia University Medical Center, 161 Fort Washington Ave, 10-1068, New York, NY 10032; e-mail: [email protected].

Author Contributions

Conception and design: Dawn L. Hershman, William E. Barlow, Joseph Unger
Financial support: Dawn L. Hershman
Collection and assembly of data: Dawn L. Hershman, Joseph Unger
Data analysis and interpretation: Cathee Till, Jason D. Wright, Danielle Awad, Scott D. Ramsey, William E. Barlow, Lori M. Minasian, Joseph Unger
Manuscript writing: All authors
Final approval of manuscript: All authors

Disclosures

Authors’ disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article.

Metrics & Citations

Metrics

Altmetric

Citations

Article Citation

Download Citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format





Download article citation data for:
Dawn L. Hershman, Cathee Till, Jason D. Wright, Danielle Awad, Scott D. Ramsey, William E. Barlow, Lori M. Minasian, Joseph Unger
Journal of Clinical Oncology 2016 34:25, 3014-3022

View Options

View options

PDF

View PDF

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Personal login Institutional Login

Purchase Options

Purchase this article to get full access to it.

Purchase this Article

Subscribe

Subscribe to this Journal
Renew Your Subscription
Become a Member

Media

Figures

Other

Tables

Share

Share

Share article link

Share