The changing causal foundations of cancer-related symptom clustering during the final month of palliative care: A longitudinal study

<p>Abstract</p> <p>Background</p> <p>Symptoms tend to occur in what have been called symptom clusters. Early symptom cluster research was imprecise regarding the causal foundations of the coordinations between specific symptoms, and was silent on whether the relationships between symptoms remained stable over time. This study develops a causal model of the relationships between symptoms in cancer palliative care patients as they approach death, and investigates the changing associations among the symptoms and between those symptoms and well-being.</p> <p>Methods</p> <p>Complete symptom assessment scores were obtained for 82 individuals from an existing palliative care database. The data included assessments of pain, anxiety, nausea, shortness of breath, drowsiness, loss of appetite, tiredness, depression and well-being, all collected using the Edmonton Symptom Assessment System (ESAS). Relationships between the symptoms and well-being were investigated using a structural equation model.</p> <p>Results</p> <p>The model fit acceptably and explained between 26% and 83% of the variation in appetite, tiredness, depression, and well-being. Drowsiness displayed consistent effects on appetite, tiredness and well-being. In contrast, anxiety's effect on well-being shifted importantly, with a direct effect and an indirect effect through tiredness at one month, being replaced by an effect working exclusively through depression at one week.</p> <p>Conclusion</p> <p>Some of the causal forces explaining the variations in, and relationships among, palliative care patients' symptoms changed over the final month of life. This illustrates how investigating the causal foundations of symptom correlation or clustering can provide more detailed understandings that may contribute to improved control of patient comfort, quality of life, and quality of death.</p

Gender and respiratory factors associated with dyspnea in chronic obstructive pulmonary disease

RATIONALE: We had shown that COPD women expressed more dyspnea than men for the same degree of airway obstruction. OBJECTIVES: Evaluate gender differences in respiratory factors associated with dyspnea in COPD patients. METHODS: In a FEV(1 )% matched population of 100 men and women with COPD we measured: age, MMRC, FEV(1), FVC, TLC, IC/TLC, PaO(2), PaCO(2), D(LCO), P(imax), P(0.1), Ti/Ttot, BMI, ffmi, 6MWD and VAS scale before and after the test, the Charlson score and the SGRQ. We estimated the association between these parameters and MMRC scores. Multivariate analysis determined the independent strength of those associations. RESULTS: MMRC correlated with: BMI (men:-0.29, p = 0.04; women:-0.28, p = 0.05), ffmi (men:-0.39, p = 0.01), FEV(1 )% (men:-0.64, p < 0.001; women:-0.29, p = 0.04), FVC % (men:-0.45, p = 0.001; women:-0.33, p = 0.02), IC/TLC (men:-0.52, p < 0.001; women: -0.27, p = 0.05), PaO(2 )(men:-0.59, p < 0.001), PaCO(2 )(men:0.27, p = 0.05), D(LCO )(men:-0.54, p < 0.001), P(0.1)/P(imax )(men:0.46, p = 0.002; women:0.47, p = 0.005), dyspnea measured with the Visual Analog Scale before (men:0.37, p = 0.04; women:0.52, p = 0.004) and after 6MWD (men:0.52, p = 0.002; women:0.48, p = 0.004) and SGRQ total (men:0.50, p < 0.001; women:0.59, p < 0.001). Regression analysis showed that P(0.1)/P(imax )in women (r(2 )= 0.30) and BMI, DL(CO), PaO(2 )and P(0.1)/P(imax )in men (r(2 )= 0.81) were the strongest predictors of MMRC scores. CONCLUSION: In mild to severe COPD patients attending a pulmonary clinic, P(0.1)/P(imax )was the unique predictor of MMRC scores only in women. Respiratory factors explain most of the variations of MMRC scores in men but not in women. Factors other than the respiratory ones should be included in the evaluation of dyspnea in women with COPD

Lung cancer diagnosed following an emergency admission: exploring patient and carer perspectives on delay in seeking help

Purpose Compared to others, patients diagnosed with lung cancer following an emergency, unplanned admission to hospital (DFEA) have more advanced disease and poorer prognosis. Little is known about DFEA patients’ beliefs about cancer and its symptoms or about their help-seeking behaviours prior to admission. Methods As part of a larger single-centre, prospective mixed-methods study conducted in one University hospital, we undertook qualitative interviews with patients DFEA and their carers to obtain their understanding of symptoms and experiences of trying to access healthcare services before admission to hospital. Interviews were recorded and transcribed. Framework analysis was employed. Results Thirteen patients and 10 carers plus 3 bereaved carers took part in interviews. Three patient/carer dyads were interviewed together. Participants spoke about their symptoms and why they did not seek help sooner. They described complex and nuanced experiences. Some (n = 12) had what they recalled as the wrong symptoms for lung cancer and attributed them either to a pre-existing condition or to ageing. In other cases (n = 9), patients or carers realised with hindsight that their symptoms were signs of lung cancer, but at the time had made other attributions to account for them. In some cases (n = 3), a sudden onset of symptoms was reported. Some GPs (n = 6) were also reported to have made incorrect attributions about cause. Conclusion Late diagnosis meant that patients DFEA needed palliative support sooner after diagnosis than patients not DFEA. Professionals and lay people interpret health and illness experiences differently

Changes in symptom clusters in patients undergoing radiation therapy

The goals of the study were to determine the occurrence rates for and the severity of symptoms at the middle, end, and 1 month after the completion of radiation therapy (RT), to determine the number and types of symptom clusters at these three time points, and to evaluate for changes over time in these symptom clusters. Symptom occurrence and severity were evaluated using the Memorial Symptom Assessment Scale (MSAS) in a sample of patients (n = 160) who underwent RT for breast or prostate cancer. At each time point, an exploratory factor analysis was done to determine the number of symptom clusters (i.e., symptom factors) based on the MSAS symptom severity ratings. The majority of the patients were male and married with a mean age of 61.1 years. The five symptoms with the highest occurrence rates across all three time points were lack of energy, pain, difficulty sleeping, feeling drowsy, and sweats. Although the number of symptoms and the specific symptoms within each symptom cluster were not identical across the three time points, three relatively similar symptom clusters (i.e., “mood-cognitive” symptom cluster, “sickness-behavior” symptom cluster, “treatment-related”, or “pain” symptom cluster) were identified in this sample. The internal consistency coefficients for the mood-cognitive symptom cluster and sickness-behavior symptom cluster were adequate at ≥0.68. Three relatively stable symptom clusters were found across RT. The majority of the symptom cluster severity scores were significantly higher in patients with breast cancer compared to patients with prostate cancer

Global Assessment of Functioning (GAF): properties and frontier of current knowledge

ABSTRACT: BACKGROUND: Global Assessment of Functioning (GAF) is well known internationally and widely used for scoring the severity of illness in psychiatry. Problems with GAF show a need for its further development (for example validity and reliability problems). The aim of the present study was to identify gaps in current knowledge about properties of GAF that are of interest for further development. Properties of GAF are defined as characteristic traits or attributes that serve to define GAF (or may have a role to define a future updated GAF). METHODS: A thorough literature search was conducted. RESULTS: A number of gaps in knowledge about the properties of GAF were identified: for example, the current GAF has a continuous scale, but is a continuous or categorical scale better? Scoring is not performed by setting a mark directly on a visual scale, but could this improve scoring? Would new anchor points, including key words and examples, improve GAF (anchor points for symptoms, functioning, positive mental health, prognosis, improvement of generic properties, exclusion criteria for scoring in 10-point intervals, and anchor points at the endpoints of the scale)? Is a change in the number of anchor points and their distribution over the total scale important? Could better instructions for scoring within 10-point intervals improve scoring? Internationally, both single and dual scales for GAF are used, but what is the advantage of having separate symptom and functioning scales? Symptom (GAF-S) and functioning (GAF-F) scales should score different dimensions and still be correlated, but what is the best combination of definitions for GAF-S and GAF-F? For GAF with more than two scales there is limited empirical testing, but what is gained or lost by using more than two scales? CONCLUSIONS: In the history of GAF, its basic properties have undergone limited changes. Problems with GAF may, in part, be due to lack of a research programme testing the effects of different changes in basic properties. Given the widespread use, research-based development of GAF has not been especially strong. Further research could improve GAF