Systemic Lupus Erythematosus May Be a Risk Factor for Antimalarial-Induced Retinopathy Compared With Other Rheumatologic Diseases.

OBJECTIVE: To describe the pattern and risk factors for antimalarial (AM)-induced retinopathy in patients with rheumatic diseases. METHODS: A retrospective chart review was conducted at an urban Canadian center for patients with AM use of more than 3 months and documented retinopathy screening. Univariate and multivariate regression analyses were performed to determine risk factors for retinopathy. Sensitivity analyses included stratification of analysis by method of screening and by hydroxychloroquine (HCQ) versus chloroquine (CQ). RESULTS: A total of 613 patients were included in the final analysis, with systemic lupus erythematosus (SLE) (n = 259) as the most common diagnosis. Definite AM-induced retinal toxicity was observed in 12 patients, 11 of whom had SLE. The earliest diagnosis of toxicity occurred after 5.4 years of AM therapy, and the prevalence beyond 5 years was 3.1%. In univariate analysis, a diagnosis of SLE (P = 0.009; odds ratio [OR]: 15.66; 95% confidence interval [CI]: 2.01-122.05), the daily weight-based dose of HCQ (P = 0.044; OR: 1.49; 95% CI: 1.01-2.20), cumulative CQ dose (P = 0.014; OR: 4.80; CI: 1.37-16.84), and daily CQ weight-based dose (P = 0.0001; OR: 5.70; 95% CI: 2.41-13.49) were significantly associated with toxicity. In multivariate analysis, diagnosis of SLE (P = 0.022; OR: 12.14; 95% CI: 1.44-102.44) and daily CQ weight-based dose (P = 0.005; OR: 1.83; 95% CI: 1.83-26.75) were significant after adjusting for standard covariates. CONCLUSION: The risk of AM-induced retinopathy increases after 5 years of therapy. There may be higher rates of toxicity in patients with SLE because of longer duration of treatment, higher weight-based dosages, and more CQ use in this population, and SLE may be an independent risk factor.

Guidelines on prescribing and monitoring antimalarials in rheumatic diseases: a systematic review.

OBJECTIVES: The purpose of this systematic review was to identify existing guidelines for antimalarial prescribing and monitoring, specifically for hydroxychloroquine, and how these guidelines compare and have evolved over time. METHODS: A literature search was conducted using Embase and Medline to identify guidelines published from 1946-2018. MeSH terms were used and alternative spelling and related words were entered as keywords to broaden results. RESULTS: 243 results were reviewed to obtain 11 recommendations. Ophthalmology sources included the American Academy of Ophthalmology, Royal College of Ophthalmologists and Canadian editorials. The American College of Rheumatology and Canadian Rheumatology Association consensus statements summarised rheumatology recommendations. Recently, American and British guidelines changed from suggesting hydroxychloroquine doses ≤6.5 mg/kg/day to ≤5 mg/kg/day. American guidelines recommended baseline visual field (VF) testing and annual screening after five years. Visual field (VF) testing evolved from the Amsler grid to current recommendations of 10-2 automated VF and spectral-domain optical coherence tomography (SD-OCT). The 2012 Canadian recommendations suggested initial VF testing every two years, with SD-OCT after 10 years. Older British guidelines advocated for baseline and annual assessment with Amsler grids during rheumatology clinic visits. The 2018 British guidelines supported baseline and annual screening after five years with 10-2 VF, SD-OCT and fundus autofluorescence. CONCLUSIONS: The newest recommendations are heterogeneous suggesting lower hydroxychloroquine dosing. Retinal toxicity is irreversible and the risk increases over time. Annual screening after five years with automated VF and SD-OCT may be warranted to detect early changes and discontinue therapy if necessary.

Neoadjuvant treatments for locally advanced, resectable esophageal cancer: A network meta-analysis.

The relative survival benefits and postoperative mortality among the different types of neoadjuvant treatments (such as chemotherapy only, radiotherapy only or chemoradiotherapy) for esophageal cancer patients are not well established. To evaluate the relative efficacy and safety of neoadjuvant therapies in resectable esophageal cancer, a Bayesian network meta-analysis was performed. MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials were searched for publications up to May 2016. ASCO and ASTRO annual meeting abstracts were also searched up to the 2015 conferences. Randomized controlled trials that compared at least two of the following treatments for resectable esophageal cancer were included: surgery alone, surgery preceded by neoadjuvant chemotherapy, neoadjuvant radiotherapy or neoadjuvant chemoradiotherapy. The primary outcome assessed from the trials was overall survival. Thirty-one randomized controlled trials involving 5496 patients were included in the quantitative analysis. The network meta-analysis showed that neoadjuvant chemoradiotherapy improved overall survival when compared to all other treatments including surgery alone (HR 0.75, 95% CR 0.67-0.85), neoadjuvant chemotherapy (HR 0.83. 95% CR 0.70-0.96) and neoadjuvant radiotherapy (HR 0.82, 95% CR 0.67-0.99). However, the risk of postoperative mortality increased when comparing neoadjuvant chemoradiotherapy to either surgery alone (RR 1.46, 95% CR 1.00-2.14) or to neoadjuvant chemotherapy (RR 1.58, 95% CR 1.00-2.49). In conclusion, neoadjuvant chemoradiotherapy improves overall survival but may also increase the risk of postoperative mortality in patients locally advanced resectable esophageal carcinoma.

A systematic literature analysis of correlative studies in low-dose metronomic chemotherapy trials.

Low-dose metronomic (LDM) chemotherapy is a beneficial and very well-tolerated form of chemotherapy utilization characterized by the frequent and uninterrupted administration of low doses of conventional chemotherapeutic agents over prolonged periods of time. While patients resistant to standard maximum tolerated dose (MTD) chemotherapy may still benefit from LDM chemotherapy, there is a lack of predictive markers of response to LDM chemotherapy. We searched the MEDLINE, EMBASE, CENTRAL and PubMed databases for correlative studies conducted as part of LDM chemotherapy trials in order to identify the most promising biomarker candidates. Given the antiangiogenic properties of LDM chemotherapy, angiogenesis-related biomarkers were most commonly studied. However, significant correlations between angiogenesis-related biomarkers and study end points were rare and variable, even so far as biomarkers correlating positively with an end point in some studies and negatively with the same end point in other studies. Pursuing biomarkers outside the angiogenesis field may be more promising.

Chemotherapy-induced cardiotoxicity: detection, prevention, and management.

Chemotherapy-induced cardiotoxicity is a major cause of morbidity and mortality in cancer survivors. It might manifest as arrhythmia, hypertension, myocardial ischemia, thromboembolism, heart failure, systolic dysfunction, or other adverse events. Anthracyclines and trastuzumab are the chemotherapeutic agents with the most documented cardiac side effects; however, the array of novel molecular targeting therapies available is concerning because their side effects are not yet well understood. Nevertheless, there are potential strategies to mitigate the risks of cardiac complications for cancer patients. In this article, the common systemic drugs with cardiotoxic potential and the monitoring and diagnostic tools, including the role of biomarkers for early detection, are reviewed. We will also review the use of cardioprotectant agents as pharmacological interventions in prophylactic and treatment settings. Our aim is to provide a concise and up-to-date summary of the detection, management, and prevention of chemotherapy-induced cardiotoxicity for the busy clinician.

Predictive factors of overall quality of life in advanced cancer patients using EORTC QLQ-C30.

OBJECTIVE: To identify which domains/symptoms from the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) were predictive of overall quality of life (QoL) in advanced cancer patients. METHODS: Four hundred and forty seven patients with brain metastases or bone metastases from seven countries were enrolled with regression analysis to determine the predictive value of the QLQ-C30 functional/symptom scores for patient reported overall QoL (question 30), overall health (question 29) and the global health status domain (questions 29 and 30). RESULTS: Worse role functioning, social functioning, fatigue and financial problems were the most significant predictive factors for worse QoL. In the bone metastases subgroup (n = 400), role functioning, fatigue and financial problems were the most significant predictors. In patients with brain metastases (n = 47), none of the EORTC domains significantly predicted worse QOL. CONCLUSION: Deterioration of certain QLQ-C30 functional/symptom scores significantly contributes to worse QoL, overall health and global health status.

Predictive factors for overall quality of life in patients with advanced cancer.

OBJECTIVE: This study examined which domains/symptoms from the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 15 Palliative (QLQ-C15-PAL), an abbreviated version of the health-related EORTC QLQ-C30 questionnaire designed for palliative cancer patients, were predictive of overall quality of life (QOL) in advanced cancer patients. METHODS: Patients with advanced cancer from six countries completed the QLQ-C15-PAL at consultation and at one follow-up point. Univariate and multivariate regression analyses were conducted to determine the predictive value of the EORTC QLQ-C15-PAL functional/symptom scores for global QOL (question 15). RESULTS: Three hundred forty-nine patients completed the EORTC QLQ-C15-PAL at baseline. In the total patient sample, worse emotional functioning, pain, and appetite loss were the most significant predictive factors for worse QOL. In the subgroup of patients with bone metastases (n = 240), the domains mentioned above were also the most significant predictors, whereas in patients with brain metastases (n = 109), worse physical and emotional functioning most significantly predicted worse QOL. One-month follow-up in 267 patients revealed that the significant predictors changed somewhat over time. For example, in the total patient sample, physical functioning, fatigue, and appetite loss were significant predictors at the follow-up point. A sub-analysis of predictive factors affecting QOL by primary cancer (lung, breast, and prostate) was also conducted for the total patient sample. CONCLUSION: Deterioration of certain EORTC QLQ-C15-PAL functional/symptom scores significantly contributes to worse overall QOL. Special attention should be directed to managing factors most influential on overall QOL to ensure optimal management of advanced cancer patients.

Symptom clusters using the Spitzer quality of life index in patients with brain metastases--a reanalysis comparing different statistical methods.

PURPOSE: The purpose of this paper is to determine whether the use of three different statistical methods influences the composition of symptom clusters derived from patients with brain metastases. MATERIALS AND METHODS: The dataset previously compiled from 129 brain metastases patients who completed the Spitzer Quality of Life Index (SQLI) and an additional study-designed 17-item symptom questionnaire was employed in this study. Symptom clusters extracted using principal component analysis in our previous study were compared to clusters determined using hierarchical cluster analysis and exploratory factor analysis. Clusters were identified using the three statistical methods at baseline, and at 1, 2, and 3 months following whole brain radiotherapy. RESULTS: The number and composition of symptom clusters at each time point varied based on the statistical method employed, despite the use of an identical dataset. However, some domains consistently clustered together, such as activity and daily living from the SQLI items. Of the 17 additional symptoms, memory loss, confusion, and trouble concentrating were always present in the same cluster. Nausea and vomiting also occurred in conjunction regardless of the analytical method employed. CONCLUSION: Symptom clusters vary with respect to occurrence, quantity, and composition based on the statistical method utilized to extract them. Further studies should be conducted to determine an ideal statistical method in order to select the optimal method to employ. The use of a single analytical method is essential for consistency and comparison purposes in future symptom cluster research.

Symptom clusters in patients with advanced cancer: a reanalysis comparing different statistical methods.

CONTEXT: The clinical relevance of symptom cluster research remains questionable if inconsistencies, partially attributable to the varying statistical analyses used, exist. OBJECTIVES: To investigate whether symptom clusters identified were consistent using three different statistical methods and to observe the temporal pattern of clusters. A secondary objective was to compare symptom clustering in responders and nonresponders to radiotherapy over time. METHODS: Reanalysis of an existing data set compiled from 1296 patients with advanced cancer was performed using hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) to extract symptom clusters at baseline, 1-, 2-, 4-, 8-, and 12-week follow-up time points. Findings were compared with results obtained using principal component analysis (PCA) in our previously published study. The original sample was further divided into two subgroups: responders and nonresponders. The symptom clusters present in each subgroup were examined using PCA, HCA, and EFA at the same time points as mentioned above. RESULTS: The symptom cluster findings of HCA and PCA correlated more frequently with each other than either did with the results of EFA. Complete consensus in all three statistical methods was never reached at any assessment time point in the present study. Increasingly diverging patterns of symptom cluster development over time were observed in the responder vs. nonresponder subgroups. Symptom pairs comprising anxiety and depression or fatigue and drowsiness consistently presented in the same cluster despite the shifting of other symptoms in the cluster over time. CONCLUSION: The presence and composition of symptom clusters identified varied depending on which statistical analysis method was used. A key step in achieving consistency in symptom cluster research involves the utilization of a common analytical method.

Projected referral to other healthcare services in an outpatient palliative radiotherapy clinic.

AIMS: To investigate the projected referral to other healthcare services in an outpatient palliative radiotherapy clinic. METHODS: Patients referred for palliative radiotherapy from 1999 to 2002 inclusive and 2007 to 2009 inclusive were evaluated. The Edmonton Symptom Assessment System, which assesses nine symptoms, was completed by 1439 patients prior to radiotherapy consultation. The numeric scale was converted into a categorical scale of none, mild, moderate and severe. Patients with moderate-to-severe symptoms were identified as potential referrals to other healthcare services. RESULTS: Tiredness (66%), poor sense of wellbeing (64%), pain (57%) and poor appetite (52%) had the most patients scoring in the moderate-to-severe range. Moderate-to-severe anxiety and depression occurred in 39 and 30% of patients, respectively, reflecting the percentage of projected referrals for symptom and/or psychosocial management. CONCLUSION: Cancer symptoms are complex, and a multidisciplinary and collaborative approach should be taken to provide timely management and maintain patients' quality of life.

Symptom clusters in patients with bone metastases--a reanalysis comparing different statistical methods.

PURPOSE: The aims of this study were to determine whether symptom clusters in patients with bone metastases varied when derived using three different statistical methods and to compare the presentation of symptom clusters over time in responders and nonresponders to palliative radiation treatment (RT). METHODS: Secondary analysis of a previously reported data set compiled using the brief pain inventory from 348 patients with bone metastases. Hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) were performed to identify symptom clusters at baseline, 1, 2, and 3 months following radiation treatment. Clusters derived were compared with the findings obtained using principal component analysis (PCA) in our previous study. The total patient sample was further separated into two subgroups: responders and nonresponders to RT. PCA, HCA, and EFA identified symptom clusters experienced by each subgroup at the same time points as before. RESULTS: Little correlation was observed in the symptom cluster findings of PCA, EFA, and HCA in the total patient sample. Absolute consensus among all three statistical methods was never reached at any assessment time point in the present study. Varying patterns of symptom cluster presentation over time were observed in the responders versus nonresponders subgroups regardless of the analytical method employed. A core cluster of symptoms composed of worst pain, general activity, walking ability, normal work, and enjoyment of life frequently presented in the same cluster. CONCLUSION: The presence and composition of symptom clusters derived varied depending on which statistical analysis method was employed. A key step in attaining consistency in symptom cluster research necessitates the utilization of a common method.

Symptom Clusters in Patients With Bone Metastases: A Sub-Analysis of Patients Reporting Exclusively Non-Zero BPI Scores.

BACKGROUND: The use of different statistical methods and inclusion criteria when deriving symptom clusters in cancer patients are contributing factors in cluster inconsistencies across studies. Primary objective was to extract symptom clusters in a subgroup of patients reporting non-zero Brief Pain Inventory (BPI) scores at baseline, and to compare clusters with those identified in the total patient sample. METHODS: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA) were performed on the non-zero subgroup and total patient sample to identify symptom clusters at baseline and 1, 2 and 3 months following radiotherapy. RESULTS: At baseline, different symptom clusters were derived from the non-zero subgroup and the total patient population. Only PCA identified identical clusters. Over time, clusters extracted using the three statistical methods varied, with a few exceptions where the same clusters were extracted using two different methods at a specific time point. A complete consensus between all three methods was not noted at any time. The BPI, which is a short assessment tool, may lead to the extraction of oversimplified clusters. In addition, since this study analyzed results in the non-zero subgroup, clusters derived may be reflective of patients with poorer prognosis as these patients experienced all symptoms. CONCLUSION: Analyzing data compiled from all eligible consenting patients may not provide clinically relevant clustering among all symptoms in the assessment tool. The composition of symptom clusters varied with the inclusion of patients with zero symptom severity scores and with the statistical method employed.

Symptom Clusters Using the Edmonton Symptom Assessment System in Patients With Bone Metastases: A Reanalysis Comparing Different Statistical Methods.

BACKGROUND: To determine whether symptom clusters in patients with bone metastases vary when extracted using three different statistical methods. To compare the temporal composition of symptom clusters in responders versus non-responders to palliative radiation treatment. METHODS: A previous dataset of 518 bone metastases patients who completed the Edmonton Symptom Assessment System (ESAS) was used in this study. Clusters derived using Principal Component Analysis (PCA) in our previous study were compared to symptom clusters extracted using Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA). Clusters were derived at baseline, and 1, 2, 4, 8 and 12 weeks after radiation treatment. The patient sample was further divided into responders versus non-responders to radiotherapy. The three statistical methods were performed to identify clusters in the subgroups at each time point. RESULTS: A complete consensus between HCA, EFA and PCA for the number and composition of symptom clusters was not reached at any time point. Furthermore, little correlation in clusters was found between the three statistical methods despite the use of an identical data set. As expected, different symptom clusters were observed in the responders and non-responders with all three statistical methods. In addition, clusters varied at each time point within each subgroup. Depression and anxiety were consistently found in the same cluster. CONCLUSION: The quantity, composition, and occurrence of symptom clusters varied based on which statistical method was employed. The use of a common analytical method is necessary for consistency and comparison purposes in future symptom cluster research.

Symptom clusters in patients with advanced cancer: sub-analysis of patients reporting exclusively non-zero ESAS scores.

BACKGROUND: Advanced cancer patients often experience multiple concurrent symptoms, which can have prognostic effects on patients' quality of life. Including patients who did not experience all of the symptoms measured by an assessment tool may interfere with accurate symptom cluster identification. Varying statistical methods may also contribute to inconsistencies of cluster results. AIMS: To compare symptom clusters in a subgroup of patients reporting exclusively non-zero ESAS scores with those in the total patient sample. To examine whether using different statistical methods results in varied symptom clusters. DESIGN: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA) were performed on the 'non-zero' subgroup and the total patient sample to identify symptom clusters at baseline and weeks 1, 2, 4, 8 and 12 following palliative radiotherapy. SETTING/PARTICIPANTS: A previous single-centre study used Principal Component Analysis to explore symptom clusters in 1296 advanced cancer patients. The present study analyzed this previously reported data set. RESULTS: Notably different symptom clusters were extracted between the two patient groups regardless of the statistical method at baseline, with the exception of a cluster composed of drowsiness, fatigue and dyspnea using Principal Component Analysis and Hierarchical Cluster Analysis. At follow-ups, different statistical methods yielded significantly varied symptom clusters. Only anxiety, depression and well-being consistently occurred in the same cluster across methods and over time. CONCLUSIONS: The composition of symptom clusters varied depending on if patients with non-zero scores were excluded at baseline and on the statistical method employed. Identifying valid clusters may prove useful for bettering symptom diagnosis and management for cancer patients.

FACT-Br for assessment of quality of life in patients receiving treatment for brain metastases: a literature review.

INTRODUCTION: Brain metastases are a significant cause of morbidity and mortality for patients with advanced cancers, and quality-of-life (QoL) end points are most appropriate for this population. The Functional Assessment of Cancer Therapy (FACT) questionnaires are commonly used to assess cancer-related QoL issues. The FACT-Brain (FACT-Br) provides an additional set of disease-specific questions pertaining to brain neoplasms. We aim to provide a comprehensive review to examine the use of the FACT-Br as a QoL assessment for patients with brain metastases. MATERIALS & METHODS: A review of the literature was conducted and all studies utilizing the FACT-Br for QoL assessment of patients with brain metastases were included. Study information and relevant information regarding the FACT-Br were extracted. RESULTS: A total of 14 studies were identified representing various treatment options (radiation, chemotherapy and surgery) for patients with brain metastases. All studies utilized at least part of the FACT-Br as the main QoL assessment. In addition, neurocognitive and performance status assessments were performed in nine and 12 out of 14 studies, respectively. Issues of poor accrual, compliance and attrition were common and posed problems in reaching statistically significant changes in QoL despite changes in raw QoL scores. CONCLUSION: Studies involving patients with brain metastases should continue to utilize QoL tools such as the FACT-Br; however, this tool still requires validation for use in this patient population. Additional studies should observe the relationship between neurocognitive function and QoL, and attempt to minimize poor accrual and compliance issues through modifications of trial design and reduction of patient burden.

A literature review of symptom clusters in patients with breast cancer.

The aim of this article is to present a review reporting empirically determined symptom clusters in breast cancer patients. We conducted a literature search on symptom clusters in breast cancer patients using PubMed, MEDLINE, EMBASE and CINAHL. Studies examining the presence of predetermined clusters were excluded. The five relevant studies identified were published between 2005 and 2009. The five studies differed from each other by statistical methodology, by the number of symptom clusters produced and by the symptoms comprising the clusters. Symptom clusters extracted between the five studies varied from one to four, while the number of symptoms in a cluster ranged from two to five. One study examining symptom clusters between different patient groups and a second study examining clusters across a time trajectory had certain reproducible clusters comprising similar symptoms. There were no clusters across different studies that contained the same symptoms, although the single symptom of fatigue was present in a cluster in all five studies and depression/psychological distress was noted in four of the studies. Nausea and appetite were the only two symptoms that associated together across three of the five studies; however, they were not the only two symptoms in those clusters. Methodological disparities include different patient populations between and within studies, different statistical methods, varying assessment tools and time points, with the majority of studies employing more than one symptom tool. Although there were common symptoms assessed across the five studies, no common symptom clusters could be derived from these reports. This lack of commonality may result from the disparities in subpopulations of patients, assessment tools, and analytical and methodological approaches. As symptom cluster research continues to develop towards a clearer consensus on guidelines, the findings of symptom clusters may provide clinically valuable information regarding diagnosis, prognostication, prioritizing and managing symptoms in breast cancer patients.

Comparison of the EORTC QLQ-C15-PAL and the FACIT-Pal for assessment of quality of life in patients with advanced cancer.

Shorter quality-of-life (QoL) assessments are beneficial for palliative patients as they reduce burden associated with completing personal, and at times stressful, questionnaires. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative (QLQ-C15-PAL) and the Functional Assessment of Chronic Illness Therapy - Palliative Care (FACIT-Pal) are two palliative QoL tools that have been validated for use in this population. The purpose of this article was to conduct a review of studies utilizing these two palliative-specific QoL instruments, their development and their relative strengths for use in advanced cancer patients. Studies detailing the development process for the QLQ-C15-PAL and the FACIT-Pal were identified. A comparison between both questionnaires in terms of development, characteristics, validation and use was conducted. The QLQ-C15-PAL was developed via structured shortening of the longer core instrument, the Quality of Life Questionnaire Core 30 (QLQ-C30), whereas the FACIT-Pal includes the Functional Assessment of Cancer Therapy - General tool plus a new 19-item palliative scale created through interviews with patients and healthcare professionals. Although significant overlap exists between both tools, there is a marked difference in the aspects of QoL assessed. Scoring, organization and item format are different; however, response options and recall period are the same. Both tools cover the core items relevant to patients with advanced cancers and can be supplemented with disease-specific tools. Both QLQ-C15-PAL and FACIT-Pal allow for assessment of QoL issues specific to patients with advanced diseases. Each instrument has unique strengths and weaknesses and choice between these tools is dependent on the investigator and study needs. Future studies should directly compare these two tools and validate their use through a number of administration modes.

Symptom clusters in patients with lung cancer: a literature review.

OBJECTIVE: To provide a review of literature reporting empirically determined symptom clusters in lung cancer patients. METHOD: We conducted a literature search on symptom clusters in lung cancer patients using MEDLINE, EMBASE and CINAHL. Studies examining the presence of predetermined clusters were excluded. The five relevant studies identified were published between 1997 and 2009. RESULTS: Overall, the five studies reported significantly diverse findings with regards to symptom cluster quantity and composition in lung cancer patients. The number of symptom clusters extracted varied from one to four per study. The number of symptoms in a cluster ranged from two to 11. The only cluster that was consistently identified in two studies was composed of nausea and vomiting symptoms. Respiratory clusters identified in two studies were also comparable, containing both dyspnea and cough, among other symptoms. Methodological disparities, including differences in sample population characteristics, assessment tools and analytical methods, were evident in the five studies reviewed. CONCLUSION: Symptom cluster exploration is a developing area of research in the oncology field and is promising in providing insights into diagnosis, prognostication and symptom management. Disparities in methodology are significant barriers to producing comparable results. These inconsistencies result in a lack of consensus in symptom clusters in lung cancer populations, thus impeding the determination of clinically relevant findings.

Poor Accrual in Palliative Research Studies: An Update From the Rapid Response Radiotherapy Program.

BACKGROUND: In June 2003, the Rapid Response Radiotherapy Program (RRRP) implemented changes to recruitment strategies in attempts to increase patient accrual to research studies. Such modifications included the use of a dedicated research assistant to screen for and identify eligible study patients, the introduction of more appropriate inclusion criteria, and the switch towards telephone interviews to minimize patient burden. The purpose of this study is to provide an update on patient accrual in the RRRP. METHODS: All patients seen in the RRRP from January 2002 to December 2009 were recorded in a prospective database. Reasons for referral, eligibility for clinical trials, reasons for non-accrual, and various demographics information were recorded. Descriptive statistics summarized findings. RESULTS: A total of 4726 patient visits were recorded from January 1st, 2002 to December 31st, 2009. Prior to changes, the overall rate of accrual into research studies was 14.9% versus 48.1% after changes were implemented. Patients were not accrued onto studies mainly to due ineligibility according to study protocol. Other reasons such as language barrier (12.1%), physician objection (3.5%), patient declining participation (11.3%) and lack of a research assistant (9.3%) were cited. CONCLUSIONS: Changes in clinical structure and study design can significantly impact accrual patterns in palliative radiotherapy studies. Despite these changes however, the majority of patients are still not enrolled in studies. Therefore additional efforts need to be made to maximize patient accrual and minimize attrition.

Symptom Clusters in Cancer Patients With Bone Metastases: Subanalysis of Patients Reporting Exclusively Non-zero ESAS Scores.

BACKGROUND: To identify symptom clusters in a subgroup of patients reporting exclusively non-zero Edmonton Symptom Assessment System (ESAS) scores at baseline, and to compare clusters with those identified in the total patient population. Secondary objective was to determine whether symptom clusters in patients with bone metastases vary when extracted using different statistical methods. METHODS: An existing dataset compiled from bone metastases patients was used to identify a "non-zero" subgroup of patients reporting severity scores > 0 for all nine ESAS symptoms at baseline. Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA) were performed on the non-zero subgroup to derive symptom clusters at baseline and 1, 2, 4, 8 and 12 weeks following radiation treatment. Symptom clusters in the total patient sample at baseline were also derived using the three statistical methods. RESULTS: At baseline, different symptom clusters were identified in the non-zero subgroup compared with the total patient population regardless of the statistical method utilized. When comparing clusters derived using different statistical methods, symptom cluster results varied depending on the method employed, with a few exceptions where analogous clusters were derived using two different statistical methods at a specific time point. A complete consensus between all three methods was never observed. Only two ESAS symptoms, anxiety and depression, consistently occurred in the same cluster across different methods and over time. CONCLUSION: Compiling data from all eligible consenting patients may not provide an accurate overview of clustering among all the symptoms included in the assessment tool. The quantity and composition of symptom clusters identified varied based on whether patients with zero symptom severity scores were included at baseline and which statistical method was utilized.