Survival In Terminal Cancer Patients Research Articles

Palliative Sedation in End-of-Life Patients in Eastern Asia: A Narrative Review.

Although palliative sedation (PS) is a common practice in the palliative care of cancer patients in Western countries, there is little related research on the practice in Korea. PS can be classified into several categories according to sedation level and continuity. PS is clearly distinct from euthanasia. While euthanasia is illegal and regarded as unethical in Korea, there is little ethical and legal controversy about PS in terms of the doctrine of double effect. Most studies have asserted that PS does not shorten the survival of terminal cancer patients. Since preference for PS heavily depends on stakeholder value, it should be preceded by shared decision-making through full communication among the patient, family members, and medical team. This is a narrative review article analyzing previous studies, especially from the three Eastern Asian countries, Korea, Japan and Taiwan, which share similar cultures compared with Western countries. Practical issues concerning PS—for example, prevalence, type and dosage of medications, salvage medication, timing of its initiation, and assessment—are described in detail.

Changes in the palliative performance scale may be as important as the initial palliative performance scale for predicting survival in terminal cancer patients.

The accurate estimation of expected survival in terminal cancer patients is important. The palliative performance scale (PPS) is an important factor in predicting survival of hospice patients. The purpose of this study was to examine how initial status of PPS and changes in PPS affect the survival of hospice patients in Korea. We retrospectively examined 315 patients who were admitted to our hospice unit between January 2017 and December 2018. The patients were divided based on the PPS of ≥50% (group A) and ≤40% (group B). We performed survival analysis for factors associated with the length of survival (LOS) in group A. Based on the hospice team's weekly evaluation of PPS, we examined the effect of initial levels and changes in group A on the prognosis of patients who survived for 2 weeks or more. At the time of admission to hospice, 265 (84.1%) patients were PPS ≥50%, and 50 (15.9%) were PPS ≤40%. The median LOS of PPS ≥50% and PPS ≤40% were 15 (2-158 days) and 9 (2-43 days), respectively. Male, gastrointestinal cancer, and lower initial PPS all predicted poor prognosis in group A. Male, gastrointestinal cancer, and a PPS change of 10% or greater, compared with initial status 1 week and 2 weeks of hospitalization, were all predictors of poor prognosis in group A patients who survived for 2 weeks or longer. Our research demonstrates the significance of PPS change at 1 week and 2 weeks, suggesting the importance of evaluating not only initial PPS but also change in PPS.

Kanser hastalarında sağkalım Palyatif Performans Skalası ile doğru olarak tahmin edilebilir mi?

Introduction: Palliative Performance Scale (PPS), Karnofsky Performance Scale (KPS) and the Edmonton Symptom Assessment Scale (ESAS) are widely used prognostic scales in palliative care unit. Institutionalized palliative care services in our country are quite new compared to the practices in many countries. We do not have concrete data on the compatibility of these scales, which are developed with patient data from other countries, in our own palliative care practices with real cases. In this study, we aimed to evaluate the convenience of the Turkish versions of these scales on the first days of hospitalization of terminal cancer patients who were followed up in the palliative clinic of our hospital. We also questioned whether the initial estimated survival and actual survival were compatible. Methods: PPS, KPS and ESAS on the first days of hospitalization of terminal cancer patients, hospitalized in the palliative clinic of our hospital between November 14, 2016 and November 14, 2017, were retrospectively evaluated one year later (n = 222). The survivors and those who lost their lives were determined. The survival estimates with PPS of the patients who died were compared with their actual survival.Results: The average age of 222 patients (18% female, 82% male) participating in the study was 64.49 ± 11.62, and the range was 26-91. PPS, KPS, ESAS were determined as a mean value of 34.40±18.00 (min. 10-max. 90), 32.90±17.50 (min. 10-max. 90), 56.10±15.65 (min. 2-max. 90), respectively. The AUC of PPS is 0.83 (p<0.001) and the AUC of KPS is 0.78 (p<0.001) suggesting that KPS and PPS has at least one tie between alive and dead patients, which is 45%. Median survival time was found 14.00, 95% C.I. [10.87–17.13]. Conclusion: In our study, it was found that as the KPS and PPS scores decrease, the survival time of terminal cancer patients decrease. Patients with PPS <45% had a higher risk of death (sensitivity 71%, specificity 80%), patients with KPS <45% had a higher risk of death (sensitivity 60%, specificity 81%), and patients with ESAS> 60.50 had a higher risk of death (sensitivity 93%, specificity 45%). PPS is a useful assessment scale for predicting survival of terminal cancer patients in the palliative care unit. We think it is important in determining our patient-specific palliative approach and treatments.

Differential Diagnosis of Cachexia and Refractory Cachexia and the Impact of Appropriate Nutritional Intervention for Cachexia on Survival in Terminal Cancer Patients.

Cancer cachexia subsequently shifts to refractory cachexia, however, it is not easy to properly differentiate them in clinical settings. Patients considered refractory cachexia may include cachectic patients with starvation. This study aimed to identify these cachectic patients and to evaluate the effect of nutritional intervention for them. Study subjects were terminal cancer patients admitted for palliative care and were judged refractory cachexia in the last five years. We retrospectively examined to find useful indices for identifying such cachectic patients and for evaluating the effect of nutritional intervention. Out of 223 patients in refractory cachexia, 26 were diagnosed cachexia with starvation after symptom management. Comparing before and one week after this management, Palliative Performance Scale (PPS) and transthyretin significantly improved (p < 0.0001, p = 0.0002, respectively) Then, we started nutritional intervention for these cachectic patients and divided into effective group (n = 17) and non-effective group (n = 9) using the criteria for cachexia. Comparing between the two groups, PPS significantly improved2 weeks after intervention in effective group (p = 0.006). Survival time was significantly longer in effective group (p = 0.008). PPS and transthyretin were useful for differential diagnosis of cachexia and refractory cachexia. PPS was useful for evaluating nutritional intervention for cachectic patients. Appropriate nutritional intervention improved survival.

1509P Impact of differential diagnosis of cachexia and refractory cachexia and appropriate nutritional support for cachexia on survival in terminal cancer patients

1509P Impact of differential diagnosis of cachexia and refractory cachexia and appropriate nutritional support for cachexia on survival in terminal cancer patients

Relationship between patient-generated subjective global assessment and survival in patients in palliative care.

A significant number of cancer deaths is partly due to late diagnosis of the disease at an advanced stage beyond cure. In this context, by applying the adequate tools, palliative care provides terminal cancer patients with the proper support for survival with a higher quality of life. The objective of this study was to describe the nutritional profile of terminal cancer patients and to evaluate the relationship among Patient-Generated Subjective Global Assessment (PG-SGA) score, clinical-functional characteristics and survival. The present work is a retrospective cohort study with 104 terminal cancer patients. The Karnofsky Performance Status (KPS) was used to obtain socio-demographic data and clinical history and assess functional capacity. Furthermore, patients were classified by groups and PG-SGA score ranges. In the first medical consultation, the PG-SGA revealed that most patients were moderately or severely malnourished and in critical need of immediate symptom management. Functional capacity of almost half of all patients lay within a KPS score of 40 to 70. Survival analysis revealed that the median time of mortality by cancer was 5 (3.3-6.7) months. Furthermore, patients with an SGA-C, i.e., severely malnourished (P<0.001), a PG-SGA score ≥9 (P=0.036) and a KPS score ≤40 (P<0.001) had a lower median time of survival. In addition to evaluating nutritional status, the PG-SGA is directly related with survival in terminal cancer patients. The use of this tool in the studied population is of paramount importance to provide individualised and adequate support for these patients.

A novel scoring system to predict survival in patients with advanced pancreatic adenocarcinoma: The Memorial Sloan Kettering Cancer Center (MSKCC) Prognostic Score (MPS).

4105 Background: A major limitation of several common prognostic tools, e.g. the Eastern Cooperative Oncology Group (ECOG), Karnofsky, and Palliative Performance Scales, is a reliance on subjective clinical assessment. An objective tool, the Glasgow Prognostic Score (GPS) derived from C-reactive Protein (CRP) and albumin levels, has been validated in patients with operable and inoperable malignancies but has the disadvantage that CRP is not routinely measured in the United States. We examined if the Neutrophil-Lymphocyte Ratios (NLR) (Ahn, H.K., et al., Neutrophil-Lymphocyte Ratio Predicts Survival in Terminal Cancer Patients. J Palliat Med, 2016) could be substituted for CRP in the GPS to predict survival in patients with advanced pancreatic adenocarcinoma. Methods: A retrospective review chart identified patients at MSKCC with pathology-confirmed stage IV pancreatic adenocarcinoma diagnosed between 2011 to 2014. Pre-treatment absolute neutrophil count, absolute lymphocyte count, and albumin were extracted. The NLR for each patient was calculated and assigned NLR ≤ 4 a value of 0; NLRs &gt; 4 a value of 1, serum albumin &gt; 4 g/dl assigned a value of 0; and serum albumin &lt; 4 g/dl assigned a value of 1. Combining NLR and albumin scores results in a composite MPS score of 0-2, similar to GPS. We evaluated the association of the MPS with overall survival. Results: N = 833 patients were identified with median survivals in the table below. A log-rank test showed statistically significant differences in survival between MPS groups (p &lt; 0.00005). The MPS on univariate analysis had a HR of 1.36 (95% CI 1.23 – 1.50, p &lt; 0.0005) associated with overall survival. Conclusions: The MPS, a composite of NLR and albumin, is an objective prognostic tool that divided this sample of patients into three clinically and statistically significant subgroups. Further interrogation will control for performance status, disease characteristics and therapy. [Table: see text]

End-of-life chemotherapy and adherence to ASCO’s Top Five List recommendations: A single-center retrospective review.

e21509 Background: End-of-life palliative chemotherapy does not improve quality of life nor does it prolong survival of terminal cancer patients. On the contrary, it is related not only to increased health costs, but also to severe therapy related side effects and to patient and caregiver distress. The first point of the ASCO’s Top Five List, released in 2012, tried to address the issue of chemotherapy overuse near the end of life. We tried to determine the aggressiveness of end of life care at our Institute by evaluating the number of patients who received end-of-life chemotherapy. We also aimed to verify whether the recent ASCO recommendations were followed or not. Methods: Electronic medical records were examined to identify patients who received at least one cycle of palliative chemotherapy and who died either in the Oncology or in the Palliative Care unit of the ICS Maugeri hospital between January 2014 and December 2015. Results: 181 patients were included in the study. 22% (40 patients) of these received chemotherapy in the last 4 weeks, and 6% (10 patients) in the last 2 weeks of life. 45% (18) of patients who were actively treated in the last month of life began a new chemotherapeutic regimen within the same period of time. Recently diagnosed patients were more likely to be treated aggressively in their last weeks of life (chi-square test, p value = 0.007). 12% of patients (7 patients) who started a new chemotherapeutic regimen within 90 days of death had already received 3 or more previous regimens. Futhermore, 16% of them (19 patients) had an ECOG PS of 3 or 4 at the beginning of the last regimen. The median survival since the beginning of the last chemotherapeutic regimen was 63 days for patients with a PS of 1 or 2 and 32 days for patients with a PS of 3 or 4 (Logrank test, p = 0.005). Conclusions: Almost 1 patient out of 4 receives end-of-life chemotherapy at our institute. About 30% of our patients began a new chemotherapeutic regimen even though they were in compromised clinical conditions or did not respond to 3 or more previous regimens. Our data highlight a relevant abuse of active anticancer treatments; efforts should be done to reduce these figures and to focus on supportive care near the end of life.

Utility of clinico-biological data for long-term prognosis of head and neck terminal cancer

Objective: The prognosis of terminal head and neck cancer is traditionally determined using indices such as the palliative prognosis index. We aimed to develop an alternative prognosis index using clinico-biological data.Methods: This retrospective case-series study included 33 head and neck cancer patients whose cancer recurred despite receiving radiation therapy between April 2010 and April 2014. Clinico-biological data were collected the day patients were diagnosed as terminal. Bivariate correlation analyses were performed on survival times and clinico-biological data. For multivariate regression analyses, patients were divided into two groups: (1) patients who survived >120 days, and (2) those who survived <120 days. Group clinico-biological data were used to determine survival-time cutoff points for the prognosis index.Results: Bivariate analyses revealed significant correlations between survival time and BMI, hemoglobin, albumin, C-reactive protein (CRP), Onodera’s Prognostic Nutritional Index (O-PNI), modified Glasgow Prognostic Score (mGPS), and Performance Status (PS). Multivariate analyses showed a strong correlation between survival time and BMI. The two groups differed significantly in BMI, albumin, CRP, O-PNI, and mGPS. In multivariate analyses BMI, CRP, and O-PNI differed significantly in the two groups.Conclusion: BMI ≤16.4, CRP ≥1.01, and O-PNI ≤33.4 are significant predictors of long-term survival in terminal cancer patients.

A novel scoring system to predict survival in patients with advanced pancreatic adenocarcinoma: The Memorial Prognostic Score (MPS).

36 Background: A major limitation of prognostic tools such as the Eastern Cooperative Oncology Group (ECOG), Karnofsky, and Palliative Performance Scale is a reliance on subjective clinical assessment. An objective tool, the Glasgow Prognostic Score (GPS) is derived from C-reactive Protein (CRP) and albumin and has been validated in patients with operable and inoperable malignancies. One disadvantage of this tool is that CRP is not routinely measured in the United States. We examined if the Neutrophil-Lymphocyte Ratios (NLR) (Ahn, H.K., et al., Neutrophil-Lymphocyte Ratio Predicts Survival in Terminal Cancer Patients. J Palliat Med, 2016) could be substituted for CRP in the GPS to predict survival in patients with advanced pancreatic adenocarcinoma. Methods: A retrospective chart review identified patients at MSKCC with pathology-confirmed stage IV pancreatic adenocarcinoma diagnosed between 2011 to 2014. Pre-treatment absolute neutrophil count, absolute lymphocyte count, and albumin were extracted. The NLR for each patient was calculated and assigned: NLR ≤ 4 g/dl = 0, NLR &gt; 4 g/dl = 1; serum albumin &gt; 4 g/dl = 0, and serum albumin &lt; 4 g/dl = 1. Combining NLR and albumin scores resulted in a composite MPS score of 0-2, similar to GPS. We evaluated the association of the MPS with overall survival. Results: N = 833 patients were identified with median survivals summarized in the table below. A log-rank test showed statistically significant differences in survival between MPS groups (p&lt;0.00005). The MPS on univariate analysis had a HR of 1.36 (95% CI 1.23 – 1.50, p&lt;0.0005) associated with overall survival. Conclusions: The MPS, a novel composite of NLR and albumin, is an objective prognostic tool that divided this sample of patients into three clinically distinct subgroups. Further interrogation will control for performance status, disease characteristics and anti-cancer therapy. [Table: see text]

Association between the duration of palliative care service and survival in terminal cancer patients

Preliminary studies of early palliative care showed improved quality of life, less medical cost, and better survival time. But, most terminal cancer patients tend to be referred to palliative care late. For the proper care of terminal cancer patients, it is necessary to refer to hospice and palliative care timely. The aim of this study is to analyze the effect of the duration of palliative care services on the survival in terminal cancer patients. We reviewed 609 patients who had died from terminal cancer between January 2010 and December 2012. We analyzed correlations of age, first Palliative Performance Scale (PPS) level, duration of palliative care service, and survival time. The Cox proportional hazards regression model was used for both univariate and multivariate analyses of survival. Duration of palliative care services was significantly correlated with survival time. In univariate Cox regression analysis, age, and each group of duration of palliative care service showed significant associations with survival. Final multivariate Cox regression model retained four parameters as independent prognostic factors for survival (age HR = 0.99 (p = 0.002), 1∼10 days HR = 2.64 (p < 0.001), 11∼30 days HR = 2.43 (p < 0.001), 31∼90 days HR = 1.87 (p < 0.001)). Shorter duration of palliative care services showed poor prognostic factor. Timely referral system from the end of chemotherapy is warranted.

Validation of the prognosis in palliative care study predictor models in terminal cancer patients.

BackgroundPrognosis in Palliative Care Study (PiPS) predictor models were developed in 2011 to estimate the survival of terminal cancer patients in the United Kingdom. The aim of this study was to validate the PiPS model for terminal cancer patients in Korea, and evaluate its value in clinical practice.MethodsThis study included 202 advanced cancer patients who were admitted to the cancer hospital's palliative care ward from November 2011 to February 2013. On admission, physicians recorded the PiPS-A, PiPS-B, and doctor's survival estimates in inpatients.ResultsThe median survival across PiPS-A categories was 9, 28, and 33 days, and the median survival across PiPS-B was 9.5, 27, and 43 days. The median actual survival was 25 days; overall accuracy between the PiPS-A, PiPS-B, doctor's estimates of survival, and actual survival was 52.0%, 49.5%, and 46.5%, respectively. The PiPS-A and PiPS-B groups for survival in 'days' showed a sensitivity of 48.4% and 64.1%, and specificity of 87.7%, and 77.5%, respectively. The PiPS-A and PiPS-B groups for survival in 'weeks' showed a sensitivity of 59.2%, and 44.7%, and specificity of 61.6%, and 64.7%, respectively. The PiPS-A and PiPS-B 'months' group showed a sensitivity of 37.1% and 37.1%, and specificity of 74.9% and 78.4%, respectively. The 'weeks' and 'months' groups showed significantly prolonged survival rates than 'days' group did in both PiPS-A and PiPS-B, by the Kaplan-Meier method.ConclusionThe PiPS predictor models effectively predicted the survival ≥14 days in terminal cancer patients, and were superior to doctor's estimates.

Estudio comparativo de la escala Palliative Prognostic Score y la estimación de los médicos en la supervivencia de la enfermedad oncológica terminal

ObjectiveTo examine the experience in the routine use of the Palliative Prognostic Score (PaP score) as a predictor of survival in terminal cancer patients and to compare it with the estimation of the patients’ survival made by doctors, as well as comparing this with the actual survival of the patients. The survival data provided by the scale are also analyzed, together with the specific characteristics of the studied group. MethodsA prospective study was conducted on 100 consecutive patients with advanced terminal cancer admitted to a Hospital Palliative Care Unit. The PaP score was applied by 2 physicians, with at least 15 years experience, when the patients were admitted. This scale assesses 6 variables that give a score that classifies patients into 3 different probabilistic groups of survival at one month. One of these 6 variables was the physician's estimation, which was analyzed and compared with the predictions of the scale. The data were collected in a database and analyzed using IBM-SPSS version 18. Medians of survival were analyzed for each group established by the PaP score, and were compared with the actual and physician's predictions. The Spearman correlation coefficient between survivals was calculated by linear regression.The differences between the evaluations made by the 2 doctors were not compared as this was not the reason for the study. ResultsOf the 100 patients analyzed, the scale distinguished 3 different probabilistic groups of survival, analyzing the percentage of compliance to the scale:Group A; high probability of surviving one month, with a total number of 13 patients. In this group only 53.8% of cases survived.Group B; intermediate probability of surviving one month, with a total number of 32 patients, where the 90% of patients did not survive for one month.Group C; with low probability of surviving one month, with a total number of 55 patients, where the 96.4% of the cases did not survive for one month.The median survival, estimated by the scale (SE), estimated by the physician (SM), and the actual survival of patients (SR) was calculated.In group A, with a SE of 33 days, the SR was 31.69 days, and SM was 79.48 days; in group B with a SE of 13.5 days, the SR was 17.53 days and the SM was 48.36 days, and in group C with a SE of 7 days, the SR was 10.36 days with an SM of 21.7 days.In group A, the doctors overestimated 2.5 times above the actual survival, while in group B and C it was overestimated 2.75 and 2.09 times, respectively.The Spearman correlation coefficient between the actual and predicted survival by physicians was 0.64, indicating a good correlation, although with a tendency to overestimate. ConclusionsPaP score scale predictions were acceptably fulfilled in all 3 groups classified by the scale. The survival estimated by an experienced physician had an acceptable correlation when compared with actual survival, although with a tendency to overestimate. When the prognosis was worse, the physician predictions were better.

Accuracy of Clinicians’ Prediction of Survival and Prognostic Factors Indicative of Survival: a Systematic Review

Objectives: To review the literature and examine the accuracy of clinicians’ prediction of survival as well as prognostic factors determined to be predictive of shorter survival in terminal cancer patients. Methods: A literature search was conducted on MEDLINE (1 January 2000 to 29 July 2012), Embase (1 January 2000 to 22 July 2012), and Cochrane Database of Systematic Reviews (1 January 2005 to July 2012). Reference sections of relevant reviews were also examined for relevant articles. All studies examining the accuracy of prediction of survival and prognostic factors indicative of survival in patients with terminal cancer were selected. Descriptive statistics summarised the extracted data. Results: A total of 85 studies published from 1972 to July 2012 with a study cohort of 30 to 6066 patients were identified. Clinicians’ prediction of survival correlated with patient’s actual survival, but the predictions tended to be too optimistic. The ability of varying health care professionals to estimate survival was contradictory among different studies. Some studies noticed those with more experience with terminal cancer patients were better able to predict an accurate estimation, whereas others concluded that there was no difference. The estimations were also more accurate during short-term time ranges such as the ‘horizon effect’. Only a few assessment tools to assist in predicting the remaining duration of survival in patients were validated. A variety of prognostic factors between studies were identified, but the factors were not validated nor any instruments created. Conclusion: Demographic information and clinical symptoms can assist in determining the remaining duration of survival of terminal cancer patients. Assessment tools should be convenient and not a burden for the patient as the goal of palliative care is to maintain or improve the quality of life as much as possible. Even with the application of instruments to formulate a prediction, error cannot be completely eliminated. Physicians should warn the patient and their family of the uncertainty of the predictions.

Prognostication Based on the Change in the Palliative Prognostic Index for Patients With Terminal Cancer

ContextThe use of the Palliative Prognostic Index (PPI) in relation to the clinical time course has not yet been established. ObjectivesTo investigate the association between the changes in the PPI over time and the survival of terminal cancer patients in a palliative care unit (PCU). MethodsThis retrospective cohort study analyzed data from 374 terminal cancer patients who were admitted to the PCU of a university hospital in Japan. Clinical data, such as age, gender, body mass index, vital signs, initial PPI, and subsequent PPI, were collected from the medical records. The PPI change per day (ΔPPI) was calculated using the initial PPI at admission and the one after five to seven days. The factors associated with death within three weeks were identified using Cox proportional hazards model analysis. ResultsAfter their admission to the PCU, 147 (39.3%) patients were deceased within three weeks. The multivariate-adjusted analysis showed that body temperature (hazard ratio [HR] 0.7; 95% CI 0.5, 1.0), initial PPI (HR 1.3; 95% CI 1.2, 1.4), and ΔPPI (HR 6.6; 95% CI 4.9, 9.0) were significantly and independently associated with death within three weeks. In the subanalysis, the ΔPPI was significantly associated with death within three weeks in the group with initial PPI ≤ 4 (HR 9.3; 95% CI 5.8, 15.0), 4 < initial PPI ≤ 6 (HR 14.4; 95% CI 5.7, 36.2), and initial PPI > 6 (HR 9.0; 95% CI 4.1, 20.0). ConclusionOur data suggest that the ΔPPI may be useful for predicting the survival of terminally ill cancer patients.

Validation of a Palliative Prognostic Index to Predict Life Expectancy for Terminally Ill Cancer Patients in a Hospice Consultation Setting in Taiwan

The aim of our study was to assess the practical utility of the palliative prognostic index (PPI) as a prognostic tool used by nurse specialists in a hospice consultation setting in Taiwan. In total, 623 terminal cancer patients under hospice consultation care from one medical center in northern Taiwan were enrolled between January 1 and June 30, 2011. PPI was assessed by a nurse specialist at first hospice consultation and patients categorized into groups by prognosis (good, intermediate, poor). Patient survival was analyzed retrospectively to determine significance of between-group differences. By PPI sum score, 37.2% of patients were in the good prognosis group, 18% in the intermediate prognosis group and 44.8% in the poor prognosis group. The death rates were 56%, 81.2% and 89.6% and median survivals were 76, 18 and 7 days, respectively. The hazard ratio was 0.19 (95% confidence interval [CI] 0.10-0.24, p<0.001) for the poor versus good prognosis group and 0.54 (95% CI 0.43-0.69, p<0.001) for the poor versus intermediate prognosis group. The sensitivity and specificity for the poor prognosis group was 66% and 71%; the positive predictive value and negative predictive value were 81% and 52%, respectively, to predict patient death within 21 days (area under the curve of the receiver operating characteristic was 0.68). Assessment by PPI can accurately predict survival of terminal cancer patients receiving hospice consultation care. PPI is a simple tool and can be administered by nurse members of hospice consultation teams.

Prediction of survival in terminal cancer patients in Taiwan: constructing a prognostic scale

We prospectively identified prognostic factors and developed a prognostic scale in 356 Taiwanese terminal cancer patients (training set). Demographic data, severity of symptoms/signs, and survival were statistically analyzed to create the scale, which was tested in another 184 patients (testing set). In the training set, liver and lung metastases, functional performance status, weight loss, edema, cognitive impairment, tiredness, and ascites were independently associated with shorter survival (multivariate analysis). The scale ranged from 0.0 (no altered variables) to 8.5 (maximal alteration for all variables). When scores were <3.5, 2-week survival was predicted with 0.72 and 0.61 accuracy for the training and testing sets, respectively. With scores <6.0, 1-week survival was predicted with 0.72 and 0.66 accuracy, respectively. This scale, which includes lung and liver metastases and severity of symptoms/signs, may help in identifying the stage of dying and its corresponding symptoms/signs and also in improving survival prediction in terminal cancer patients.

Pain severity and survival of terminal cancer patients

8030 Background: Studies suggest that cancer patients with severe and/or poorly controlled pain have shorter survivals. Whether this is related to poor pain control or the advanced state of disease is less clear. To further evaluate this, a retrospective analysis examined the survival of cancer patients admitted to hospice with different levels of pain and the effects on survival of controlling pain within 48 hours. Methods: From 4/1/02 to 3/31/03, 41,712 patients were admitted to hospices of Vitas Healthcare Corporation, a national hospice company. At each patient contact, caregivers record patient-generated pain severity scores based on a Visual Analog Scale (range 0–10) in the Vitas clinical database. Of the 41,712 patients, 8,680 patients had cancer, had an initial pain reading recorded on admission, and died by 7/24/03. Patients were grouped based on initial pain scores: Severe (7–10); Moderate (4–6); Mild (1–3); or None (0). Survival curves were compared using the Gehan-Wilcoxon statistic. Results: Initial pain levels were similar across types of cancer. Median survival for all study patients was 18 days (range 1–429). Median survival for patients admitted with severe or moderate pain was significantly shorter than for those with mild or no pain (see table). A subset of 5,168 patients had one or more pain readings on Day 2. Patients with severe pain that was reduced to 5 or less within 48 hours had a significantly longer median survival compared to patients whose pain remained greater than 5 (18 vs. 12 days, p < .001). Conclusions: Even in the face of terminal cancer, uncontrolled pain on presentation adversely affects patient survival. Rapid reduction of severe pain may offer a small but significant survival advantage. Extrapolating these results to patients earlier in the course of disease emphasizes the importance of effective and rapid pain control in all cancer patients. No significant financial relationships to disclose.

Pain severity and survival of terminal cancer patients

8030 Background: Studies suggest that cancer patients with severe and/or poorly controlled pain have shorter survivals. Whether this is related to poor pain control or the advanced state of disease...

Appropriate time frames for data collection in quality of life research among cancer patients at the end of life.

Longitudinal research has been recommended as the most appropriate research design to ensure the validity of quality of life assessments. However, high attrition and non-random missing data in quality of life studies for terminal cancer patients raise questions about generalizability of the study, and at worst they may jeopardize interpretation of the results. Appropriate time frames for eliciting information directly from terminal cancer patients can ensure the internal and external validity of quality of life research in end-of-life care, allow health care professionals to detect sensitively the effects of end-of-life care within the shortest intervention period, and make comparisons across studies possible. From a review of the literature, it is recommended that the appropriate time frame for interviewing terminal cancer patients about their quality of life be a weekly assessment schedule based on the following factors: (a) the median survival of terminal cancer patients enrolling in a hospice/palliative care program is approximately 30 days and there are substantial number of patients who die in each week; (b) at the final weeks of life, quality of life and symptoms of some terminal cancer patients change dramatically; and (c) the shortest intervention period that is likely to give a clinically significant effect of end-of-life care management is 1 week after the enrollment in end-of-life care.