Basil Kasimis

Cancer breakthrough pain characteristics and responses to treatment at a VA medical center.

&NA; The purpose of this study is to analyze cancer breakthrough pain (BP) characteristics and how BP responds to conventional cancer pain management. Seventy‐four cancer pain patients with worst pain severity ≥4 out of 10 completed the Brief Pain Inventory (BPI), Memorial Symptom Assessment Scale‐Short Form, Functional Assessment Cancer Therapy and Breakthrough Pain Questionnaires (BPQ) at an initial interview. Agency for Health Care Policy and Research (AHCPR) cancer pain management guidelines were followed. Pain syndromes and morphine equivalent daily dose (MEDD) orally were determined. One‐week follow‐up assessments were obtained in 66 patients with BPI and BPQ. The BP characteristics were similar at both time points. On day 1, 52 patients (70%) had BP, and the BP was unpredictable in 30 patients (58%). The median time to worst BP severity was 3 min. Patients with BP had significantly higher worst pain (P<0.001). At week 1, the median MEDD doubled from 60 to 120 mg orally, and the number of patients who received adjuvant analgesics doubled from 31.1% (23 patients) on day 1 to 62.2% (41 patients). At week 1, 21 patients (32%) remained without BP, 21 patients (32%) were classified as BP responders and 24 patients (36%) were BP non‐responders. The mean pain relief was similar for all three subgroups, i.e. around 80%. Compared to BP responders, BP non‐responders had significantly higher worst pain (P<0.0001), average pain (P<0.004), and higher BPI interference parameters and shorter time to worst pain severity. The study confirmed the applicability of the BPQ to an US veteran population, and that pain management following the AHCPR guidelines is effective for a group of patients with cancer related BP. Underlying pain syndromes and the BP location may influence the response of BP to treatment. Patients with bone pain located in the spine, back, and pelvis may be at risk for resistant BP.

Multidimensional independent predictors of cancer-related fatigue☆

The purpose of this study was to identify independent predictors of clinically significant fatigue based upon a multidimensional model. A total of 180 cancer patients completed the Brief Fatigue Inventory (BFI), Functional Assessment of Cancer Therapy-Fatigue (FACT-F), Memorial Symptom Assessment Scale Short Form (MSAS-SF), and the Zung Self-Rating Depression Scale (SDS). Additional data included Karnofsky Performance Status (KPS) score, laboratory tests, and demographic information. The BFI usual fatigue severity > or =3/10 was defined as clinically significant fatigue. Possible independent variables were identified from a biopsychosocial model of fatigue. Fishers exact test was used to univariately assess the association of each variable with clinically significant fatigue. Multiple logistic regression analyses were used to identify independent predictors of fatigue within each dimension, and then across dimensions. Fatigue was present in 113 (62%) patients, and 80 (44.4%) patients had usual fatigue > or =3/10. The unidimensional independent predictors were use of analgesics (situation dimension); hemoglobin and serum sodium (biomedical dimension); feeling drowsy, dyspnea, pain and lack of appetite (physical symptom dimension); and feeling sad and feeling irritable (psychological symptom dimension). In a multidimensional model, dyspnea, pain, lack of appetite, feeling drowsy, feeling sad, and feeling irritable predicted fatigue independently with good calibration (Hosmer Lemeshow Chi Square=5.73, P=0.68) and discrimination (area under the receiver operating characteristic curve=0.88). Physical and psychological symptoms predict fatigue independently in the multidimensional model, and superseded laboratory data. These findings support a symptom-oriented approach to assessment of cancer-related fatigue.

Longitudinal Quality of Life in Advanced Cancer Patients: Pilot Study Results from a VA Medical Cancer Center

To document quality-of-life (QOL), symptom distress and Karnofsky Performance Status (KPS) over time, 67 advanced cancer patients completed the Functional Assessment of Cancer Therapy (FACT-G) and Memorial Symptom Assessment Scale - Short Form (MSAS-SF) from the time of determination of no active anti-cancer treatment to death at 3-6 week intervals. The KPS was determined at each time point. Statistical analyses with mixed effects models were performed to examine the association between changes in QOL, symptom distress and KPS at selected time points in the advanced cancer trajectory. Median survival for the population was 115 days, and a median of 5 interviews was completed per patient. Slow steady changes in KPS, MSAS-SF and FACT-G QOL parameters started 6 months prior to death, with accelerated decline in the last 2 to 3 months and dramatic increase in psychological symptoms during the last month. Different domains changed at different rates at different selected time points. The correlation between changes in KPS, FACT-G parameters and MSAS-SF subscales at enrollment and near death suggests that when patients were stable, changes in KPS correlated significantly with changes in sum FACT-G QOL and physical well being, and with changes in the MSAS-SF subscales. However, when patients were near death, changes in KPS did not correlate with any other changes, and only emotional well being reflected changes in physical and psychological symptom distress. The sequence of changes, and how determinants of symptom distress and QOL change over time, may help clinicians assess the prognosis of terminally ill patients and plan appropriate interventions.

Shorter Symptom Assessment Instruments: The Condensed Memorial Symptom Assessment Scale (CMSAS)

Background. Rapid and efficient symptom assessment is an important aspect of palliative care. The objective was to determine whether a smaller number of symptoms from the 32-item Memorial Symptom Assessment Scale Short-Form (MSAS-SF) could convey equivalent quality of life (QOL) information. Methods. Responses from 479 medical oncology patients who completed the MSAS-SF and the Functional Assessment Cancer Therapy (FACT-G) were analyzed. Canonical correlations were performed to assess the relationships of 32 MSAS-SF symptoms to quality of life (FACT-G domains) and clinical variables [age, Karnofsky performance status (KPS), stage of disease, and inpatient status]. The relation of the subscales of the Condensed MSAS (CMSAS) and FACT-G to survival was assessed in a multivariate model. Results. The median age was 67 years (range, 20–89) and median KPS was 80% (range, 20–100). Primary sites were prostate in 141 (29%) patients, lung in 121 (26%) patients, colorectal in 53 (11%) patients, hematologic in 50 (10%) patients, head and neck in 30 (6%) patients and other in 84 (18%) patients. Median survival was 245 days (range, 1–2,215 days). Canonical correlation analyses identified a five-dimensional QOL factor structure. Symptoms important for QOL also correlated significantly with survival and provided the basis for the CMSAS with 14 symptoms and 3 subscales (CMSAS SUM, CMSAS PHYS, and CMSAS PSYCH). In multivariate analyses, the CMSAS PSYCH predicted survival independently of stage, performance status, and QOL. The CMSAS takes 2–4 minutes to complete. Conclusion. The CMSAS contains both QOL and survival information approximately equivalent to the original 32 items.

Prediction of Survival for Advanced Cancer Patients by Recursive Partitioning Analysis: Role of Karnofsky Performance Status, Quality of Life, and Symptom Distress

We performed an exploratory recursive partitioning analysis (RPA) in 429 metastatic cancer patients who had completed a Functional Assessment of Cancer Therapy–General (FACT-G) and a Memorial Symptom Assessment Scale–Short Form (MSAS-SF) to define survival prognostic groups. The Cox model analysis also was performed. Both RPA and Cox models included Karnofsky performance status (KPS), age, FACT-G subscales, and MSAS-SF subscales as survival predictors. Of 429 patients, 348 patients (81.1%) had expired at time of analysis. The median age was 67 years (27–89), with median length of survival of 147 days. The RPA identified four distinct survival groups (p < .0001) with three variables: KPS, physical well-being, and physical symptom distress. The most significant split was KPS of 50%, followed by physical well-being score of 25 and physical symptom distress score of 0.6. The median survival time was 29 days for patients with KPS < 50%; 146 days for patients with KPS ≥ 50% and physical well-being < 25; 292 days for patients with KPS > 50%, physical well-being ≥ 25, and physical symptom distress score > 0.6; and 610 days for patients with KPS ≥ 50%, physical well-being ≥ 25, and physical symptom distress score ≤ 0.6. The Cox model found, in addition to KPS (p < .0001) and physical well-being (p = .08), different predictors: psychological symptom distress (p = .0007), global distress index (p = .02), and age (p < .0001). We concluded that the KPS, quality of life, and symptom distress scores can be combined to define prognostic groups. Such models may be helpful for clinical decision making.

Dynamic Cancer Pain Management Outcomes: The Relationship Between Pain Severity, Pain Relief, Functional Interference, Satisfaction and Global Quality of Life Over Time

To examine the relationship between different cancer pain management outcomes over time, 74 patients with the worst cancer related pain rated as four or greater on an 11-point numeric scale were followed weekly with the Brief Pain Inventory (BPI), and the satisfaction questionnaire and global visual analogue scale quality of life (VASQOL) for 3 weeks. Univariate and multivariate regression analyses were performed at weekly time points. The analyses indicated that pain outcomes can be categorized into separate QOL and satisfaction paths linked by the worst pain severity. In the QOL path, the worst pain severity predicted a pain interference score, which consistently predicted VASQOL. For the satisfaction path, independent predictors were pain relief at Week 1, and worst pain severity and changes in worst pain severity at Week 2. No variables predicted satisfaction at Week 3. The data suggest that satisfaction and quality of life may be independent outcomes of pain management. The timing of assessment may itself be important.

Development of a Cancer Pain Prognostic Scale

The purpose of this study was to develop a Cancer Pain Prognostic Scale (CPPS) which could predict the likelihood of pain relief within 2 weeks for cancer patients with moderate to severe pain. Seventy-four (74) consecutive patients who presented with cancer-related pain were managed in accordance with the guidelines for pain management developed by the United States Agency for Health Care Policy and Research (AHCPR). Patients were followed weekly using the Brief Pain Inventory (BPI), and medications were recorded weekly for 3 weeks. Baseline scores from the Functional Assessment of Cancer Therapy (FACT-G), Mental Health Inventory (MHI), Karnofsky Performance Status (KPS), and Memorial Symptom Assessment Scale Short Form (MSAS-SF) at initial interview served as explanatory variables in a logistic regression model. Pain relief > or = 80% at the end of weeks 1 and 2 were used as outcomes in this model. From this analysis, we developed a predictive formula, the CPPS, which includes the worst pain severity, FACT-G emotional well being, daily opioid dose, and pain characteristics. The rule yields a numerical score that ranges from 0-17. Higher scores correspond to a higher probability of good pain relief. The CPPS has the potential to rapidly identify patients with poor pain prognosis. It can be used as a research tool to characterize pain in cancer patients.

A comparison of three fatigue measures in veterans with cancer.

Fatigue is a highly prevalent and distressing symptom in cancer patients. The purpose of this study was to assess the validity of three fatigue measures [the Brief Fatigue Inventory (BFI), the Functional Assessment of Cancer Therapy Fatigue Subscale (FACT-F), and the lack of energy item from the Memorial Symptom Assessment Scale Short Form (MSAS-SF)] and compare these measures in relation to broader quality-of-life (QOL) constructs and clinical factors in veteran cancer patients. One-hundred-eighty cancer patients completed the BFI, FACT-F, FACT-G, MSAS-SF, and the Zung depression scale with concurrent Karnofsky performance status (KPS), laboratory tests, and demographic data. The Cronbach alpha coefficient was from 0.93 to 0.94 for BFI fatigue scales and 0.94 for FACT-F. There were significant correlations between BFI subscales, FACT-F, and lack of energy from MSAS-SF (p<0.0001). All three fatigue measures showed significant correlation with MSAS-SF symptom subscales (p<0.0001), FACT-G subscales (p<0.0001), depression (p<0.0001), KPS (p<0.0001), inpatient status (P<0.0001), insomnia (p<0.05), hemoglobin (p<0.05), and albumin levels (p<0.01). Distress from lack of energy discriminated among levels from the BFI, FACT-F, and FACT-G subscales and MSAS-SF subsclea by one-way of variance analysis. Patient responses to BFI, FACT- F, and the lack of energy item yielded similar information about broader QOL constructs and clinical factors. Single questions about lack of energy, or fatigue severity, may provide a simple and acceptable way to assess fatigue.

Phase I Study of Flavopiridol in Combination with Paclitaxel and Carboplatin in Patients with Non-Small-Cell Lung Cancer

PURPOSE The aim of this study was to evaluate the safety and tolerability of escalating doses of flavopiridol/ paclitaxel/carboplatin in patients with advanced-stage non-small-cell lung cancer (NSCLC) as well as the pharmacokinetics and activity of flavopiridol when used in combination with paclitaxel/carboplatin. PATIENTS AND METHODS Eligible patients aged 18-75 years with previously untreated stage IIIB/IV NSCLC received paclitaxel 175 mg/m2 over 3 hours followed by carboplatin area under the curve (AUC) 5 over 1 hour and flavopiridol 30-85 mg/m2 over 24 hours every 3 weeks for 3 cycles. RESULTS Eighteen patients were enrolled at 4 sites in the United States and received flavopiridol 30 mg/m2 (n = 3), 50 mg/m2 (n = 6), 70 mg/m2 (n = 3), or 85 mg/m2 (n = 6). No dose-limiting toxicities (DLTs) occurred at the 50-mg/m2 or 70-mg/m2 dose levels. Two patients treated at the 85-mg/m2 dose level experienced cardiovascular events that did not meet the criteria for DLT but were fatal in 1 case, prompting no further flavopiridol dose escalations and establishment of 70 mg/m2 as the maximum tolerated dose. The most frequently reported adverse events across all dose levels combined were nausea (89%), asthenia (67%), and diarrhea (56%). Flavopiridol concentrations increased rapidly, reached a plateau, and showed a multiphasic decline after the 24-hour infusion. Of 12 patients evaluable for efficacy, 8 achieved a partial response, and 4 had stable disease. CONCLUSION Flavopiridol in doses <or= 70 mg/m2 in a 24-hour infusion can safely be combined with a 3-hour infusion of paclitaxel 175 mg/m2 and a 1-hour infusion of carboplatin AUC 5.

Memorial Symptom Assessment Scale

Patients with advanced illnesses often have multiple symptoms. As interest in palliative care and interventions for symptom control increase, the ability to assess multiple symptoms has become more important. A number of instruments have been developed to meet this need in cancer patients. This article reviews the development and applications of a multidimensional instrument, the Memorial Symptom Assessment Scale. The Memorial Symptom Assessment Scale has 32 symptoms and three dimensions of frequency, severity, and distress. Shorter versions – The Memorial Symptom Assessment Scale Short Form (32 symptoms with one dimension) and the Condensed Memorial Symptom Assessment Scale (14 symptoms with one dimension), and a version for children aged 7–12 years, have also been developed. A distinctive feature is the summary subscales for physical distress, psychological distress, and The Global Distress Index. The Memorial Symptom Assessment Scale has proven useful in description of symptom epidemiology, the role of symptoms in pain, fatigue, and spirituality; as a predictor of survival, and in proxy assessments of pain. The Memorial Symptom Assessment Scale has been used in studies of cancer and AIDS patients, and patients with advanced medical illnesses. Possible future roles of instruments such as the Memorial Symptom Assessment Scale include use in clinical trials, for pharmacoeconomic analyses, definition of symptom clusters and symptom burden, the development of symptom outcome measures, symptom monitoring, and improving care for patients. Continued research is needed for the versions of the Memorial Symptom Assessment Scale and other symptom instruments in different populations and applications.