Predicting survival in terminal cancer patients: clinical observation or quality-of-life evaluation?

Patient-reported symptoms and problems at admission to specialized palliative care improved survival prediction in 30,969 cancer patients: A nationwide register-based study

BACKGROUND

Large, nationally representative studies of the association between quality of life and survival time in cancer patients in specialized palliative care are missing.

AIM

The aim of this study was to investigate whether symptoms/problems at admission to specialized palliative care were associated with survival and if the symptoms/problems may improve prediction of death within 1 week and 1 month, respectively.

SETTING/PARTICIPANTS

All cancer patients who had filled in the EORTC QLQ-C15-PAL at admission to specialized palliative care in Denmark in 2010-2017 were included through the Danish Palliative Care Database. Cox regression was used to identify clinical variables (gender, age, type of contact (inpatient vs outpatient), and cancer site) and symptoms/problems significantly associated with survival. To test whether symptoms/problems improved survival predictions, the overall accuracy (area under the receiver operating characteristic curve) for different prediction models was compared. The validity of the prediction models was tested with data on 5,508 patients admitted to palliative care in 2018.

RESULTS

The study included 30,969 patients with an average age of 68.9 years; 50% were women. Gender, age, type of contact, cancer site, and most symptoms/problems were significantly associated with survival time. The predictive value of symptoms/problems was trivial except for physical function, which clearly improved the overall accuracy for 1-week and 1-month predictions of death when added to models including only clinical variables.

CONCLUSION

Most symptoms/problems were significantly associated with survival and mainly physical function improved predictions of death. Interestingly, the predictive value of physical function was the same as all clinical variables combined (in hospice) or even higher (in palliative care teams).

Prevalence and Intensity of Dyspnea in Advanced Cancer and its Impact on Quality of Life

CONTEXT

Dyspnea is a subjective, multidimensional experience of breathing discomfort, commonly seen in patients with advanced cancer. To find the impact of dyspnea on the quality of life in this population, it is important to understand the prevalence and factors influencing dyspnea.

AIMS

This study aimed to determine the prevalence, intensity, and factors influencing dyspnea in advanced cancer and determine its impact on overall quality of life.

SETTINGS AND DESIGN

This was a prospective cross-sectional study. The prevalence of dyspnea and its impact on quality of life was determined in 500 patients registered with palliative medicine outpatient department.

SUBJECTS AND METHODS

The patients were asked to fill a set of questionnaires, which included the Cancer Dyspnea Scale (translated and validated Hindi and Marathi versions), visual analog scale for dyspnea and EORTC QLQ C 15 PAL. Details of demographics, symptomatology, and medical data were collected from the case record sheets of the patients.

STATISTICAL ANALYSIS USED

Descriptive statistics, univariate, and multiple regression analysis were used to calculate the results.

RESULTS

About 44.37% of the patients experienced dyspnea. Dyspnea increased with worsening anxiety, depression, fatigue, appetite, well-being, pain, lung involvement by primary or metastatic cancer, performance status, and deteriorating overall quality of life and emotional wellbeing.

CONCLUSIONS

The prevalence of dyspnea in advanced cancer patients is as high as 44.37% and has a negative impact on their overall quality of life.

Delirium Frequency and Risk Factors Among Patients With Cancer in Palliative Care Unit

Introductıon: Delirium is a complex but common disorder in palliative care with a prevalence between 13% and 88% but a particular frequency at the end of life yet often remains insufficiently diagnosed and managed. The aim of our study is to determine the frequency of delirium and identify factors associated with delirium at palliative care unit.

METHODS

Two hundred thirteen consecutive inpatients from October 1, 2012, to March 31, 2013, were studied prospectively. Age, gender, Palliative Performance Scale (PPS), Palliative Prognostic Index (PPI), length of stay in hospital, and delirium etiology and subtype were recorded. Delirium was diagnosed with using Delirium Rating Scale (DRS) and Diagnostic and Statistical Manual of Mental Disorders, 4th Edition Text Revision ( DSM-IV TR) criteria.

RESULTS

The incidence of delirium among the patients with cancer was 49.8%. Mean age was 60.3 ± 14.8 (female 41%, male 59%, PPS 39.8%, PPI 5.9 ± 3.0, length of stay in hospital 8.6 ± 6.9 days). Univariate logistic regression analysis indicated that use of opioids, anticonvulsants, benzodiazepines, steroids, polypharmacy, infection, malnutrition, immobilization, sleep disturbance, constipation, hyperbilirubinemia, liver/renal failure, pulmonary failure/hypoxia, electrolyte imbalance, brain cancer/metastases, decreased PPS, and increased PPI were risk factors. Subtypes of delirium included hypoactive 49%, mixed 41%, and hyperactive 10%.

CONCLUSION

The communicative impediments associated with delirium generate distress for the patient, their family, and health care practitioners who might have to contend with agitation and difficulty in assessing pain and other symptoms. To manage delirium in patients with cancer, clinicians must be able to diagnose it accurately and undertake appropriate assessment of underlying causes.

Survival prediction score: a simple but age-dependent method predicting prognosis in patients undergoing palliative radiotherapy

Purpose. Validation of a Canadian three-tiered prognostic model (survival prediction score, SPS) in Norwegian cancer patients referred for palliative radiotherapy (PRT), and evaluation of age-dependent performance of the model. Patients and Methods. We analyzed all 579 PRT courses administered at a dedicated PRT facility between 20.06.07 and 31.12.2009. SPS was assigned as originally described, That is, by taking into consideration three variables: primary cancer type, site of metastases, and performance status. Results. Patients with poor prognosis (non-breast cancer, metastases other than bone, and Karnofsky performance status (KPS) ≤ 60) had median survival of 13 weeks. Those with intermediate prognosis (two of these parameters) survived for a median of 29 weeks, and patients with good prognosis for a median of 114 weeks, P < 0.001. While this model performed well in patients who were 60 years or older, it was less satisfactory in younger patients (no significant difference between the good and intermediate prognosis groups). Conclusion. SPS should mainly be used to predict survival of elderly cancer patients. However, even in this group accuracy is limited because the good prognosis group contained patients with short survival, while the poor prognosis group contained long-term survivors. Thus, improved models should be developed.

International palliative care experts' view on phenomena indicating the last hours and days of life

BACKGROUND

Providing the highest quality care for dying patients should be a core clinical proficiency and an integral part of comprehensive management, as fundamental as diagnosis and treatment. The aim of this study was to provide expert consensus on phenomena for identification and prediction of the last hours or days of a patient's life. This study is part of the OPCARE9 project, funded by the European Commission's Seventh Framework Programme.

METHOD

The phenomena associated with approaching death were generated using Delphi technique. The Delphi process was set up in three cycles to collate a set of useful and relevant phenomena that identify and predict the last hours and days of life. Each cycle included: (1) development of the questionnaire, (2) distribution of the Delphi questionnaire and (3) review and synthesis of findings.

RESULTS

The first Delphi cycle of 252 participants (health care professionals, volunteers, public) generated 194 different phenomena, perceptions and observations. In the second cycle, these phenomena were checked for their specific ability to diagnose the last hours/days of life. Fifty-eight phenomena achieved more than 80% expert consensus and were grouped into nine categories. In the third cycle, these 58 phenomena were ranked by a group of palliative care experts (78 professionals, including physicians, nurses, psycho-social-spiritual support; response rate 72%, see Table 1) in terms of clinical relevance to the prediction that a person will die within the next few hours/days. Twenty-one phenomena were determined to have "high relevance" by more than 50% of the experts. Based on these findings, the changes in the following categories (each consisting of up to three phenomena) were considered highly relevant to clinicians in identifying and predicting a patient's last hours/days of life: "breathing", "general deterioration", "consciousness/cognition", "skin", "intake of fluid, food, others", "emotional state" and "non-observations/expressed opinions/other".

CONCLUSION

Experts from different professional backgrounds identified a set of categories describing a structure within which clinical phenomena can be clinically assessed, in order to more accurately predict whether someone will die within the next days or hours. However, these phenomena need further specification for clinical use.

Preoperative estimated glomerular filtration rate predicts overall mortality in patients undergoing radical prostatectomy

BACKGROUND

Assessment of overall health is a critical component in the evaluation of patients presenting with clinically localized prostate cancer. Estimated glomerular filtration rate (eGFR) has been associated with increased risk of cardiovascular and overall mortality. Therefore, the objective of our study was to evaluate the impact of baseline renal function on oncologic outcomes and overall survival following radical prostatectomy.

MATERIALS AND METHODS

We identified 10,099 patients who underwent radical prostatectomy at our institution from 1990 to 2004 with a preoperative serum creatinine available for analysis. eGFR was calculated by the chronic kidney disease-epidemiology formula (CKD-EPI) and reported as ml/min per 1.73 m(2). Patients were then classified according to their eGFR: <30, 30-59, 60-89, 90-119, and 120-150 ml/min/1.73 m(2). Multivariate Cox proportional hazard regression models were used to analyze the impact of eGFR on postoperative outcomes.

RESULTS

At the time of surgery, 25 patients (0.1%) had an eGFR <30 ml/min/1.73 m(2), 2,398 (23.7%) between 30 and 60, 7,097 (70.3%) between 60 and 90, and 605 (6.0%) patients had an eGFR >90. eGFR was not associated with oncologic outcomes, including biochemical recurrence, systemic progression or cancer-specific survival (P > 0.05 for all). However, eGFR was strongly associated with all-cause mortality and non-prostate cancer death. On multivariate analysis, after controlling for age, BMI, prostate-specific antigen doubling time (PSA), Gleason score, and clinical stage, eGFR remains a statistically significant predictor of all-cause mortality.

CONCLUSIONS

Assessment of eGFR is an important metric in the overall evaluation of patient health and should be considered in combination with patient age and other medical comorbidities when selecting the initial treatment of prostate cancer. While prostate cancer-specific outcomes do not appear to be impacted by renal function, overall survival is decreased in those with lower and higher than normal eGFR.

Symptoms tell it all: a systematic review of the value of symptom assessment to predict survival in advanced cancer patients

PURPOSE

To determine the prognostic meaning of symptoms in patients with advanced cancer.

DESIGN

Medline, Embase, Cochrane and Cinahl databases were systematically explored. The predicting symptoms were also evaluated in the three stages of palliative care: disease-directed palliation, symptom-oriented palliation and palliation in the terminal stage.

RESULTS

Out of 3167 papers, forty-four papers satisfied all criteria. Confusion, anorexia, fatigue, cachexia, weight loss, cognitive impairment, drowsiness, dyspnea, dysphagia, dry mouth and depressed mood were associated with survival in ≥ 50% of the studies evaluating these symptoms. Multivariate analysis showed confusion, anorexia, fatigue, cachexia, weight loss, dyspnea and dysphagia as independent prognostic factors in 30-56% of the studies. In the stage of disease-directed palliation anorexia, cachexia, weight loss, dysphagia and pain and in the stage of symptom-oriented palliation confusion, fatigue, cachexia, weight loss, dyspnea, dysphagia and nausea were shown to be independent predictors of survival in >30% of the studies.

CONCLUSION

Symptoms with independent predictive value are confusion, anorexia, fatigue, cachexia, weight loss, dyspnea and dysphagia. New insights are added by the variance between the three palliative stages.

Factors influencing survival after discharge from an Australian palliative care unit to residential aged care facilities: a retrospective audit

BACKGROUND

Increasing demand for palliative care unit (PCU) beds has led to shorter inpatient stays and a requirement to transfer some patients from a PCU to a residential aged care facility (RACF). Concerns have been raised regarding this move with suggestion that patients often die shortly after transfer. Published data investigating this patient group are limited. The aim of the current study was to audit discharges from a PCU to RACFs specifically looking at predictive factors for survival following discharge.

METHODS

A retrospective audit was undertaken of all discharges from the Barwon Health PCU to RACFs between July 2007 and July 2010. Data on patient demographics, clinical and functional status, admission and discharge details, and survival times were examined. Factors influencing survival were evaluated by Cox proportional-hazards regression analysis.

RESULTS

Sixty-two discharges from a PCU to an RACF were included in the analysis. The mean age at discharge was 76 and the majority of patients had malignant disease. Mean and median survival times post-transfer were 106 and 42.5 days, respectively, and 16% of subjects survived more than 100 days. From univariate analyses age, PCU length of stay, admission Resource Utilization Groups-Activities of Daily Living (RUG-ADL) score, dependent mobility, having lung cancer or cancer of unknown primary, and living alone or in an RACF pre PCU admission affected survival. Multivariate analyses showed age, PCU length of stay, RUG-ADL score, and living situation prior to PCU admission together were associated with postdischarge survival times.

CONCLUSIONS

This study is one of the largest investigating this cohort and suggests a number of factors that may predict survival for patients after discharge from a PCU to an RACF.

Clinician accuracy when estimating survival duration: the role of the patient's performance status and time-based prognostic categories

CONTEXT

Although shown to be an independent predictor of actual survival (AS) duration, previous reports have identified significant inaccuracy in clinician estimates of survival (CES).

OBJECTIVES

This study aimed to both examine demographic and clinical factors potentially impacting CES accuracy and explore possible strategies for improvement in a patient population with advanced incurable disease.

METHODS

At the time of initial assessment by a specialist palliative care team, CES for each patient was chosen from one of the following time-based categories: <24 hours, one to seven days, one to four weeks, one to three months, three to six months, three to 12 months, or >12 months. Survival estimates were then classified as an accurate (AS=CES), overestimate (AS<CES), or underestimate (AS>CES). Demographic data were analyzed using descriptive statistics, and both univariate and stepwise multivariate logistic regression analyses were used to identify any associated demographic and/or clinical factors significantly impacting accuracy.

RESULTS

Within the total study population of 1835, both CES and AS data were available for 1622 patients among whom mean and median survival was 26.5 and 88 days, respectively. The remaining 213 patients (12% of the total population) remained alive at the time of analysis. Of the total study population, CES was accurate for 34% of patients and an overestimate for 51% of patients. CES of <24 hours and one to seven days were significantly more likely to be accurate than any other prognostic category (P<0.0001). Additionally, a CES of either one to four weeks or >12 months was significantly more likely to be accurate than CES of one to three months, three to six months, and six to 12 months (P<0.0001). Finally, multivariate analyses indicated CES to be significantly more likely to be accurate for males (P=0.0407) and for patients with baseline Palliative Performance Scale (PPS) ratings of either "30 and less" (P<0.0001) or "70 and greater" (P<0.0001).

CONCLUSION

In a patient population referred for specialist palliative care consultation with diverse diagnoses and a wide range of CES, time-based categorization of survival estimates along with PPS and possibly gender could be used to inform the CES process for individual patients. Intentionally incorporating these objective elements into what has historically been the subjective process of CES may lead to improvements in accuracy.

[Development and validation of the hospice palliative care performance scale]

PURPOSE

The purpose of this study was to develop and validate a hospice-palliative care performance measure which would cover more than just physical symptoms or quality of life.

METHODS

Through an intensive literature review, the author chose questions that measured aspects of physical, emotional, spiritual, social, or practical domains pertinent to hospice-palliative care for inclusion in the scale. Content validation of the questions was established by 15 hospice-palliative care professionals. A preliminary Hospice Palliative Care Performance Scale (HPCPS) of 20 questions was administered to 134 pairs of terminal cancer patients from 5 hospice palliative care units and their main family caregiver. A validation study was conducted to evaluate construct validity and internal consistency.

RESULTS

Factor analysis showed 14 significant questions in five subscales; Physical, Emotional, Spiritual, Social, and Patient' rights. There were no significant differences between the ratings by patients and family members except for three out of the 14 questions. The measure demonstrated construct validity, and Cronbach's alpha of the subscales ranged from .73 to .79.

CONCLUSION

The HPCOS demonstrated acceptable validity and reliability. It can be used to assess effectiveness of hospice-palliative care for terminal cancer patients in practice and research.

A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer

OBJECTIVE

The aim of the present study is to compare the accuracy in using laboratory data or clinical factors, or both, in predicting probability of dying within 7 days of hospice admission in terminal cancer patients.

METHODS

We conducted a prospective cohort study of 727 patients with terminal cancer. Three models for predicting the probability of dying within 7 days of hospice admission were developed: (i) demographic data and laboratory data (Model 1); (ii) demographic data and clinical symptoms (Model 2); and (iii) combination of demographic data, laboratory data and clinical symptoms (Model 3). We compared the models by using the area under the receiver operator curve using stepwise multiple logistic regression.

RESULTS

We estimated the probability dying within 7 days of hospice admission using the logistic function, P = Exp(betax)/[1 + Exp(betax)]. The highest prediction accuracy was observed in Model 3 (82.3%), followed by Model 2 (77.8%) and Model 1 (75.5%). The log[probability of dying within 7 days/(1 - probability of dying within 7 days)] = -6.52 + 0.77 x (male = 1, female = 0) + 0.59 x (cancer, liver = 1, others = 0) + 0.82 x (ECOG score) + 0.59 x (jaundice, yes = 1, no = 0) + 0.54 x (Grade 3 edema = 1, others = 0) + 0.95 x (fever, yes = 1, no = 0) + 0.07 x (respiratory rate, as per minute) + 0.01 x (heart rate, as per minute) - 0.92 x (intervention tube = 1, no = 0) - 0.37 x (mean muscle power).

CONCLUSIONS

We proposed a computer-assisted estimated probability formula for predicting dying within 7 days of hospice admission in terminal cancer patients.

Quality of life measures (EORTC QLQ-C30 and SF-36) as predictors of survival in palliative colorectal and lung cancer patients

OBJECTIVE

Self-reported health-related quality of life (HRQoL) is an important predictor of survival alongside clinical variables and physicians' prediction. This study assessed whether better prediction is achieved using generic (SF-36) HRQoL measures or cancer-specific (EORTC QLQ-C30) measures that include symptoms.

METHOD

Fifty-four lung and 46 colorectal patients comprised the sample. Ninety-four died before study conclusion. EORTC QLQ-C30 and SF-36 scores and demographic and clinical information were collected at baseline. Follow-up was 5 years. Deaths were flagged by the Office of National Statistics. Cox regression survival analyses were conducted. Surviving cases were censored in the analysis.

RESULTS

Univariate analyses showed that survival was significantly associated with better EORTC QLQ-C30 physical functioning, role functioning, and global health and less dyspnea and appetite loss. For the SF-36, survival was significantly associated with better emotional role functioning, general health, energy/vitality, and social functioning. The SF-36 summary score for mental health was significantly related to better survival, whereas the SF-36 summary score for physical health was not. In the multivariate analysis, only the SF-36 mental health summary score remained an independent, significant predictor, mainly due to considerable intercorrelations between HRQoL scales. However, models combining the SF-36 mental health summary score with diagnosis explained a similar amount of variance (12%-13%) as models combining diagnosis with single scale SF-36 Energy/Vitality or EORTC QLQ-C30 Appetite Loss.

SIGNIFICANCE OF RESULTS

HRQoL contributes significantly to prediction of survival. Generic measures are at least as useful as disease-specific measures including symptoms. Intercorrelations between HRQoL variables and between HRQoL and clinical variables makes it difficult to identify prime predictors. We need to identify variables that are as independent of each other as possible to maximize predictive power and produce more consistent results.

Fatigue dimensions in patients with advanced cancer in relation to time of survival and quality of life

To understand the relation between fatigue and patients emotional situation at the end of life, this cross-sectional study aimed to explore the association between multidimensional aspects of fatigue, emotional functioning and quality of life (QoL) in patients with advanced cancer at the end of life. Patients with advanced cancer answered fatigue related measurements (Borg Category Ratio-10 scale, Multidimensional Fatigue Inventory-20, Swedish Occupational Fatigue Inventory and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core-30), when admitted for specialised palliative care. A total of 228 patients with a median length of survival of 63 days were included. In relation to time of survival, fatigue increased closer to death, in both global and multidimensional aspects, as well as the patient's experience of being sleepy. Marital status was found to affect the experience of fatigue in both global and multidimensional ratings of fatigue. The association between the experience of fatigue and feelings of being tense, worried, irritable or depressed and rated QoL decreased and was not evident closer to death. Fatigue in all dimensions increased, as patients got closer to death. The association between fatigue and both QoL and negative emotions faded away during the last days and weeks of life.

Depression--an independent predictor of early death in patients with advanced cancer

OBJECTIVE

Depression is common in patients with late stage cancer. This study was carried out to investigate whether depression is associated with survival, measuring physical symptoms as a potential confounding variable.

PATIENTS AND METHODS

One hundred and thirty two patients formed the study sample and eighty-seven patients participated in the study. The Edinburgh Depression Scale (EDS) and self-rated symptoms list were completed three times over an eight-week period and analyzed, together with relevant demographic and clinical factors.

RESULTS

Depression was self-rated in 29% (25/87) of patients at the initial screen and 54.5% of surviving patients remained depressed at eight-week follow-up. No significant associations were found between baseline EDS 'caseness' and demographic factors or tumour type. However EDS scores were significantly correlated with four symptoms measures. Sixty two percent (54/87) of patients died during the 12 month period of the study. The EDS score had a significant independent effect upon risk of death in study period - a one-point increase in EDS score raises risk of outcome (death) by 7%.

CONCLUSIONS

Depression is an independent predictor of poor survival in patients with advanced cancer. It is important that patients with advanced cancer are screened for depression and appropriate interventions offered.

Predictive model for survival in patients with advanced cancer

PURPOSE

To derive and validate a simple predictive model for survival of patients with metastatic cancer attending a palliative radiotherapy clinic.

PATIENTS AND METHODS

We described previously a model predicting survival of patients referred for palliative radiotherapy using six prognostic factors: primary cancer site, site of metastases, Karnofsky performance score (KPS), and the fatigue, appetite, and shortness of breath subscales from the Edmonton Symptom Assessment Scale. Here we simplified the model to include only three factors: primary cancer site, site of metastases, and KPS. Each factor was assigned a value proportional to its prognostic weight, and the weighted scores for each patient were summed to obtain a survival prediction score (SPS). Patients were also grouped according to their number of risk factors (NRF): nonbreast cancer, metastases other than bone, and KPS < or = 60. The three- and six- variable models were evaluated for their ability to predict survival in patients referred during a different time period and of those referred to a different cancer center.

RESULTS

A training set of 395 patients, a temporal validation set of 445 patients, and an external validation set of 467 patients were used. The ability of the three- and six-variable models to separate patients into three prognostic groups and to predict their survival was similar using both SPS and NRF methods in the training, temporal, and external validation data sets. There was no statistically significant difference in the performance of the models.

CONCLUSION

The three-variable NRF model is preferred because of its relative simplicity.

Symptoms and survival in patients with advanced disease

Predicting survival in patients with advanced disease is challenging for health care providers. Accurate survival estimation using symptom assessment may assist physicians and patients in determining treatment options. This report analyzes prospective studies in adult patients with a median/mean survival of 6 months or less and identifies symptoms that are associated with decreased survival. To be included in this analysis, a study needed to have at least one symptom associated with decreased survival in a univariate or multivariate analysis. Twenty-two studies were identified and 15 symptoms were associated with decreased survival. Anorexia, delirium, and dyspnea were associated with decreased survival in most studies. Delirium and anorexia (but not dyspnea) were associated with decreased survival in most studies that included patients with a median survival of 30 days or less. More research is needed to investigate any associations between symptom characteristics and survival in patients with advanced disease. Short assessment tools using symptoms identified in this report, with a focus on symptoms that were found in multiple studies, need to be developed to better predict survival and guide patient treatment.

The Prognostic Value of Measuring Health-Related Quality of Life in Hospice Patients

PURPOSE

Better prognostic instruments are sorely needed for patients near the end of life. Health-related quality of life instruments designed for hospice patients have not been previously studied for their prognostic properties. This study evaluated the prognostic property of the Missoula-Vitas Quality of Life Index (MVQOLI) with hospice patients.

METHODS

A prospective, cross-sectional cohort design included all consecutive patients admitted to a hospice over a 19-month period. At admission to hospice, patients were asked to complete an MVQOLI. In addition, hospice nurses completed three functional status instruments. All patients were followed until death, study closure, or loss to follow-up.

RESULTS

The sample included 1047 patients, but only 231 (22%) were able to complete an MVQOLI at admission. Functional status data were collected on nearly all of the patients. The Karnofsky performance score, modified activity of daily living score, and descriptive symptom score were significantly associated with survival time. Using Cox regression models these functional status assessments were strongly associated with survival time (p<0.001). However, the MVQOLI scores were not significantly associated with survival time, except for the function subscale (p=0.045).

CONCLUSION

The MVQOLI global, total, and four of the five weighted-domain baseline scores were not associated with survival time in hospice patients. Other methods for prognostication at the end of life are needed.

Lactate dehydrogenase as a prognostic factor for survival time of terminally ill cancer patients: A preliminary study

This study evaluated lactate dehydrogenase (LDH) as a prognostic factor for survival time in terminal cancer patients. We prospectively followed 93 consecutive inpatients with terminal cancer in one general hospital. Cox's proportional hazard model was used to adjust the influence of some clinical and laboratory variables on survival time. For 25 patients, LDH levels at 2 weeks and 1 week before death were compared by paired t test. In multivariate analysis, elevated LDH level (313 IU/L) was confirmed as an unfavourable indicator for survival time (hazard ratio=2.087, p=0.002). Serum LDH levels were significantly increased as the patients approached death. A combined index comprising LDH levels, C reactive protein levels, uric acid levels, presence of moderate to severe pain, fatigue, hypotension and performance status demonstrated a good stratification value for predicting survival time. Our results showed that serum LDH level can be a useful predictor of survival time of terminally ill cancer patients.

Development of a model with which to predict the life expectancy of patients with spinal epidural metastasis

BACKGROUND

The surgical treatment of spinal epidural metastasis is evolving. To be a surgical candidate, a patient should have a life expectancy of at least 3 months. Estimation of survival by experienced specialists has proven to be unreliable.

METHODS

The Cox proportional hazards model was used to make a prediction model. To validate the model, Efron optimism correction by bootstrapping was performed. Retrospective data of patients treated for a spinal metastasis were used. Possible predictive factors were defined based on clinical experience and the literature. Statistical methods and clinical knowledge were also used to reveal an optimal set of predictors of survival. Data from patients treated at the Department of Radiation Oncology for spinal metastasis between 1998 and 2005 were evaluated.

RESULTS

The case notes of 219 patients form the base of this study. In the final model, only 5 variables were required to predict the survival of a patient with spinal metastasis: sex, location of the primary lesion, intentional curative treatment of the primary tumor, cervical location of the spinal metastasis, and Karnofsky performance score. Examples with different predictors are given. The R(2) (N) index of Nagelkerke was 0.36 (95% confidence interval [95% CI], 0.28-0.48) and the c-index 0.72 (95% CI, 0.68-0.77).

CONCLUSIONS

A reliable and simple model with which to predict the survival of a patient with spinal epidural metastasis is presented. Without the need for extensive investigations, survival can be predicted and only 5 easily obtainable parameters are required.

The Relationship Between Cognition and Mortality in Patients with Stroke, Coronary Heart Disease, or Cancer

Numerous studies have reported an association between cognitive impairment and an increased risk for mortality. Most results are from large epidemiological studies and control for medical conditions that may relate to cognitive decline, as well as an increased mortality risk. The aim of this review was to evaluate the association between cognitive performance and mortality within patient samples of stroke, cancer, or coronary heart disease. After reviewing the PubMed literature for articles on stroke, cancer, and cardiovascular related illnesses, 47 longitudinal studies were identified that met the cognition/mortality search criteria. In general, the results demonstrated that within the clinical groups studied, cognitive performance and cognitive impairment both predict mortality, although results were less consistent for coronary heart disease. This study adds further support for the ubiquity of the association of cognitive performance with health outcomes and mortality. Optimizing health has implications for both cognitive performance and longevity.

Clinically meaningful changes in health-related quality of life in patients diagnosed with hepatobiliary carcinoma

BACKGROUND

To test the reliability, sensitivity to change in biomarkers associated with disease progression and response to treatment, and clinical meaningfulness of the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep) in patients with hepatobiliary carcinoma.

PATIENTS AND METHODS

One hundred and fifty-eight patients diagnosed with hepatobiliary carcinoma were prospectively studied. Health-related quality of life (HRQL) was assessed at baseline (prior to treatment), 3-month follow-up (n=55) and 6-month follow-up (n=27).

RESULTS

The internal consistency of all the scales of the FACT-Hep were adequate at all time points (>0.75). The FACT-Hep was found to be sensitive to changes in clinical indicators (alkaline phosphate, alpha-fetoprotein, hemoglobin and survival) that reflect disease progression and response to treatment. Combined results from distribution-based and cross-sectional anchor-based analyses provide the following minimally important difference (MID) estimates: FACT-General (FACT-G) subscales=2-3; FACT-G=6-7; Hepatobiliary Cancer Subscale=5-6; FACT-Hep=8-9; Trial Outcome Index=7-8; and FACT-Hepatobiliary Symptom Index=2-3 points.

CONCLUSIONS

The FACT-Hep is a reliable instrument that is responsive to clinical indicators of disease progression and response to treatment. The MID estimates can aid interpretation of HRQL data and facilitate sample size calculation in clinical trials.