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Dive into the research topics where Dale J. Langford is active.

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Featured researches published by Dale J. Langford.


The Journal of Pain | 2012

Identification of patient subgroups and risk factors for persistent breast pain following breast cancer surgery.

Christine Miaskowski; Bruce A. Cooper; Steven M. Paul; Claudia West; Dale J. Langford; Jon D. Levine; Gary Abrams; Deborah Hamolsky; Laura B. Dunn; Marylin Dodd; John Neuhaus; Christina Baggott; Anand Dhruva; Brian L. Schmidt; Janine K. Cataldo; John D. Merriman; Bradley E. Aouizerat

UNLABELLED Study purposes were to determine the prevalence of persistent pain in the breast; characterize distinct persistent pain classes using growth mixture modeling; and evaluate for differences among these pain classes in demographic, preoperative, intraoperative, and postoperative characteristics. In addition, differences in the severity of common symptoms and quality of life outcomes measured prior to surgery, among the pain classes, were evaluated. Patients (n = 398) were recruited prior to surgery and followed for 6 months. Using growth mixture modeling, patients were classified into no (31.7%), mild (43.4%), moderate (13.3%), and severe (11.6%) pain groups based on ratings of worst breast pain. Differences in a number of demographic, preoperative, intraoperative, and postoperative characteristics differentiated among the pain classes. In addition, patients in the moderate and severe pain classes reported higher preoperative levels of depression, anxiety, and sleep disturbance than the no pain class. Findings suggest that approximately 25% of women experience significant and persistent levels of breast pain in the first 6 months following breast cancer surgery. PERSPECTIVE Persistent pain is a significant problem for 25% of women following surgery for breast cancer. Severe breast pain is associated with clinically meaningful decrements in functional status and quality of life.


The Journal of Pain | 2012

Associations between pro- and anti-inflammatory cytokine genes and breast pain in women prior to breast cancer surgery.

Birha McCann; Christine Miaskowski; Theresa Koetters; Christina Baggott; Claudia West; Jon D. Levine; Charles Elboim; Gary Abrams; Deborah Hamolsky; Laura B. Dunn; Hope S. Rugo; Marylin Dodd; Steven M. Paul; John Neuhaus; Bruce A. Cooper; Brian L. Schmidt; Dale J. Langford; Janine K. Cataldo; Bradley E. Aouizerat

UNLABELLED The purposes of this study were to determine the occurrence rate for preoperative breast pain; describe the characteristics of this pain; evaluate for differences in demographic and clinical characteristics; and evaluate for variations in pro- and anti-inflammatory cytokine genes between women who did and did not report pain. Patients (n = 398) were recruited prior to surgery and completed self-report questionnaires on a number of pain characteristics. Genotyping was done using a custom genotyping array. Women (28.2%) who reported breast pain were significantly younger (P < .001); more likely to be nonwhite (P = .032); reported significantly lower Karnofsky Performance Status scores (P = .008); were less likely to be postmenopausal (P = .012); and had undergone significantly more biopsies (P = .006). Carriers of the minor allele for a single nucleotide polymorphism in interleukin (IL)1-receptor 1 (IL1R1) (rs2110726) were less likely to report breast pain prior to surgery (P = .007). Carriers of the minor allele for a single nucleotide polymorphism in IL13 (rs1295686) were more likely to report breast pain prior to surgery (P = .019). Findings suggest that breast pain occurs in over a quarter of women who are about to undergo breast cancer surgery. Based on phenotypic and genotypic characteristics found, inflammatory mechanisms contribute to preoperative breast pain. PERSPECTIVE In women with breast cancer, preoperative pain may be associated with increases in inflammatory responses associated with an increased number of biopsies. In addition, differences in cytokine genes may contribute to this preoperative breast pain.


Biological Research For Nursing | 2015

Associations Between Cytokine Genes and a Symptom Cluster of Pain, Fatigue, Sleep Disturbance, and Depression in Patients Prior to Breast Cancer Surgery:

Sy Huey Doong; Anand Dhruva; Laura B. Dunn; Claudia West; Steven M. Paul; Bruce A. Cooper; Charles Elboim; Gary Abrams; John D. Merriman; Dale J. Langford; Heather Leutwyler; Christina Baggott; Kord M. Kober; Bradley E. Aouizerat; Christine Miaskowski

Pain, fatigue, sleep disturbance, and depression are common and frequently co-occurring symptoms in oncology patients. This symptom cluster is often attributed to the release of proinflammatory cytokines. The purposes of this study were to determine whether distinct latent classes of patients with breast cancer (n = 398) could be identified based on their experience with this symptom cluster, whether patients in these latent classes differed on demographic and clinical characteristics and whether variations in cytokine genes were associated with latent class membership. Three distinct latent classes were identified: “all low” (61.0%), “low pain and high fatigue” (31.6%), “all high” (7.1%). Compared to patients in the all low class, patients in the all high class were significantly younger, had less education, were more likely to be non-White, had a lower annual income, were more likely to live alone, had a lower functional status, had a higher comorbidity score, and had more advanced disease. Significant associations were found between interleukin 6 (IL6) rs2069845, IL13 rs1295686, and tumor necrosis factor alpha rs18800610 and latent class membership. Findings suggest that variations in pro- and anti-inflammatory cytokine genes are associated with this symptom cluster in breast cancer patients.


Sleep Medicine Reviews | 2012

Sleep disturbance interventions in oncology patients and family caregivers: A comprehensive review and meta-analysis

Dale J. Langford; Kathryn A. Lee; Christine Miaskowski

Sleep disturbance is a significant problem for both oncology patients and family caregivers (FCs), and is associated with poorer functional status, quality of life, and potentially disease progression. This review describes a comprehensive literature search and meta-analysis of the efficacy of interventions for sleep disturbance in oncology patients and their FCs. This search revealed 47 studies that evaluated the effects of a number of interventions on sleep disturbance/sleep quality, as a primary or secondary outcome in oncology patients. The primary purposes of the review were to synthesize findings from intervention studies for sleep disturbance in oncology patients and their FCs; to evaluate the efficacy of these interventions; to identify gaps in the literature; and to provide directions for future research. In addition, all 47 intervention studies were evaluated in terms of key intervention and study characteristics. Both strong patterns and inconsistencies were identified among the studies, which complicate an evaluation of the efficacy of interventions, and may collectively guide future research. Finally, the importance of including the FC in sleep disturbance interventions is discussed. In light of the detrimental effects that sleep disturbance has on both the patient and the FC, this systematic review may better inform essential future intervention efforts.


Cancer | 2014

Disease and treatment characteristics do not predict symptom occurrence profiles in oncology outpatients receiving chemotherapy

Christine Miaskowski; Bruce A. Cooper; Michelle E. Melisko; Lee-may Chen; Judy Mastick; Claudia West; Steven M. Paul; Laura B. Dunn; Brian L. Schmidt; Marilyn J. Hammer; Frances Cartwright; Fay Wright; Dale J. Langford; Kathryn A. Lee; Bradley E. Aouizerat

A large amount of interindividual variability exists in the occurrence of symptoms in patients receiving chemotherapy (CTX). The purposes of the current study, which was performed in a sample of 582 oncology outpatients who were receiving CTX, were to identify subgroups of patients based on their distinct experiences with 25 commonly occurring symptoms and to identify demographic and clinical characteristics associated with subgroup membership. In addition, differences in quality of life outcomes were evaluated.


European Journal of Oncology Nursing | 2014

Identification of patient subgroups and risk factors for persistent arm/shoulder pain following breast cancer surgery.

Christine Miaskowski; Steven M. Paul; Bruce A. Cooper; Claudia West; Jon D. Levine; Charles Elboim; Deborah Hamolsky; Gary Abrams; Judith Luce; Anand Dhruva; Dale J. Langford; John D. Merriman; Kord M. Kober; Christina Baggott; Heather Leutwyler; Bradley E. Aouizerat

PURPOSE In this prospective, longitudinal study, we extend our findings on persistent breast pain in patients (n = 398) following breast cancer surgery and evaluate the prevalence and characteristics of persistent pain in the arm/shoulder. In addition, differences in the severity of common symptoms and quality of life outcomes measured prior to surgery, among the arm pain classes, were evaluated. METHODS AND SAMPLE Patients were recruited from Breast Care Centers located in a Comprehensive Cancer Center, two public hospitals, and four community practices. Patients were assessed prior to and monthly for six months following breast cancer surgery. RESULTS Using growth mixture modeling, patients were classified into no (41.6%), mild (23.6%), and moderate (34.8%) arm pain classes based on ratings of worst arm/shoulder pain. Compared to the no pain class, patients in the moderate pain class were significantly younger, had a higher body mass index, and were more likely to report preoperative breast pain and swelling in the affected breast. In addition, patients in the moderate pain class reported higher levels of depression, anxiety, and sleep disturbance than the no pain class. CONCLUSIONS Findings suggest that approximately 35% of women experience persistent levels of moderate arm/shoulder pain in the first six months following breast cancer surgery. Moderate arm/shoulder pain is associated with clinically meaningful decrements in functional status and quality of life.


PLOS ONE | 2012

Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers

Christine Miaskowski; Bruce A. Cooper; Anand Dhruva; Laura B. Dunn; Dale J. Langford; Janine K. Cataldo; Christina Baggott; John D. Merriman; Marylin Dodd; Kathryn A. Lee; Claudia West; Steven M. Paul; Bradley E. Aouizerat

The purposes of this study were to identify distinct latent classes of individuals based on subjective reports of sleep disturbance; to examine differences in demographic, clinical, and symptom characteristics between the latent classes; and to evaluate for variations in pro- and anti-inflammatory cytokine genes between the latent classes. Among 167 oncology outpatients with breast, prostate, lung, or brain cancer and 85 of their FCs, growth mixture modeling (GMM) was used to identify latent classes of individuals based on General Sleep Disturbance Scale (GSDS) obtained prior to, during, and for four months following completion of radiation therapy. Single nucleotide polymorphisms (SNPs) and haplotypes in candidate cytokine genes were interrogated for differences between the two latent classes. Multiple logistic regression was used to assess the effect of phenotypic and genotypic characteristics on GSDS group membership. Two latent classes were identified: lower sleep disturbance (88.5%) and higher sleep disturbance (11.5%). Participants who were younger and had a lower Karnofsky Performance status score were more likely to be in the higher sleep disturbance class. Variation in two cytokine genes (i.e., IL6, NFKB) predicted latent class membership. Evidence was found for latent classes with distinct sleep disturbance trajectories. Unique genetic markers in cytokine genes may partially explain the interindividual heterogeneity characterizing these trajectories.


European Journal of Oncology Nursing | 2013

Cytokine Gene Variation is Associated with Depressive Symptom Trajectories in Oncology Patients and Family Caregivers

Laura B. Dunn; Bradley E. Aouizerat; Dale J. Langford; Bruce A. Cooper; Anand Dhruva; Janine K. Cataldo; Christina Baggott; John D. Merriman; Marylin Dodd; Claudia West; Steven M. Paul; Christine Miaskowski

PURPOSE Depressive symptoms are common in cancer patients and their family caregivers (FCs). While these symptoms are characterized by substantial interindividual variability, the factors that predict this variability remain largely unknown. This study sought to confirm latent classes of oncology patients and FCs with distinct depressive symptom trajectories and to examine differences in phenotypic and genotypic characteristics among these classes. METHOD Among 167 oncology outpatients with breast, prostate, lung, or brain cancer and 85 of their FCs, growth mixture modeling (GMM) was used to identify latent classes of individuals based on Center for Epidemiological Studies-Depression (CES-D) scores obtained prior to, during, and for four months following completion of radiation therapy. One hundred four single nucleotide polymorphisms (SNPs) and haplotypes in 15 candidate cytokine genes were interrogated for differences between the two largest latent classes. Multivariate logistic regression analyses assessed effects of phenotypic and genotypic characteristics on class membership. RESULTS Four latent classes were confirmed: Resilient (56.3%), Subsyndromal (32.5%), Delayed (5.2%), and Peak (6.0%). Participants who were younger, female, non-white, and who reported higher baseline trait and state anxiety were more likely to be in the Subsyndromal, Delayed, or Peak groups. Variation in three cytokine genes (i.e., interleukin 1 receptor 2 [IL1R2], IL10, tumor necrosis factor alpha [TNFA]), age, and performance status predicted membership in the Resilient versus Subsyndromal classes. CONCLUSIONS Findings confirm the four latent classes of depressive symptom trajectories previously identified in a sample of breast cancer patients. Variations in cytokine genes may influence variability in depressive symptom trajectories.


The Journal of Pain | 2014

Associations between cytokine gene variations and severe persistent breast pain in women following breast cancer surgery.

Kimberly Stephens; Bruce A. Cooper; Claudia West; Steven M. Paul; Christina Baggott; John D. Merriman; Anand Dhruva; Kord M. Kober; Dale J. Langford; Heather Leutwyler; Judith Luce; Brian L. Schmidt; Gary Abrams; Charles Elboim; Deborah Hamolsky; Jon D. Levine; Christine Miaskowski; Bradley E. Aouizerat

UNLABELLED Persistent pain following breast cancer surgery is a significant clinical problem. Although immune mechanisms may play a role in the development and maintenance of persistent pain, few studies have evaluated for associations between persistent breast pain following breast cancer surgery and variations in cytokine genes. In this study, associations between previously identified extreme persistent breast pain phenotypes (ie, no pain vs severe pain) and single nucleotide polymorphisms (SNPs) spanning 15 cytokine genes were evaluated. In unadjusted analyses, the frequency of 13 SNPs and 3 haplotypes in 7 genes differed significantly between the no pain and severe pain classes. After adjustment for preoperative breast pain and the severity of average postoperative pain, 1 SNP (ie, interleukin [IL] 1 receptor 2 rs11674595) and 1 haplotype (ie, IL10 haplotype A8) were associated with pain group membership. These findings suggest a role for cytokine gene polymorphisms in the development of persistent breast pain following breast cancer surgery. PERSPECTIVE This study evaluated for associations between cytokine gene variations and the severity of persistent breast pain in women following breast cancer surgery. Variations in 2 cytokine genes were associated with severe breast pain. The results suggest that cytokines play a role in the development of persistent postsurgical pain.


Biological Research For Nursing | 2015

Cytokine Gene Associations With Self-Report Ratings of Morning and Evening Fatigue in Oncology Patients and Their Family Caregivers

Anand Dhruva; Bradley E. Aouizerat; Bruce A. Cooper; Steven M. Paul; Marylin Dodd; Claudia West; William M. Wara; Kathryn A. Lee; Laura B. Dunn; Dale J. Langford; John D. Merriman; Christina Baggott; Janine K. Cataldo; Christine S. Ritchie; Kord M. Kober; Heather Leutwyler; Christine Miaskowski

The purpose of this study was to evaluate for differences in variations in pro- and anti-inflammatory cytokine genes between participants who were classified as having low and high levels of morning and evening fatigue and to evaluate for differences in phenotypic characteristics between these two groups. In a sample of 167 oncology outpatients with breast, prostate, lung, or brain cancer and 85 of their family caregivers, growth mixture modeling was used to identify latent classes of individuals based on ratings of morning and evening fatigue obtained prior to, during, and for 4 months following completion of radiation therapy. Differences in single nucleotide polymorphisms and haplotypes in 15 cytokine genes were evaluated between the latent classes. Multiple logistic regression was used to assess the effect of phenotypic and genotypic characteristics on morning and evening fatigue class membership. Associations were found between morning fatigue and number of comorbidities as well as variations in tumor necrosis factor alpha (TNFA) rs1800629 and rs3093662. Evening fatigue was associated with caring for children at home and variations in interleukin 4 (IL4) rs2243248 and TNFA rs2229094. Younger age and lower performance status were associated with both morning and evening fatigue. These findings suggest that inflammatory mediators are associated with the development of morning and evening fatigue. However, because different phenotypic characteristics and genomic markers are associated with diurnal variations in fatigue, morning and evening fatigue may be distinct but related symptoms.

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Steven M. Paul

University of California

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Claudia West

University of California

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Kord M. Kober

University of California

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Jon D. Levine

University of California

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Anand Dhruva

University of California

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