Annals of Oncology Advance Access originally published online on April 6, 2006
Annals of Oncology 2006 17(7):1083-1089; doi:10.1093/annonc/mdl065
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
© 2006 European Society for Medical Oncology
Quality of life is predictive of survival in patients with unresectable hepatocellular carcinoma
Departments of 1 Clinical Oncology and 2 Surgery, 3 Centre for Clinical Trials, Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China; 4 Cancer Research UK, Institute for Cancer Studies, University of Birmingham, UK
* Correspondence to: Dr W. Yeo, Department of Clinical Oncology, Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR, China. Tel: +852-2632-2118; Fax: +852-2648-7097; E-mail: winnieyeo{at}cuhk.edu.hk
| Abstract |
|---|
|
|
|---|
Background: Patients with unresectable hepatocellular carcinoma (HCC) have a dismal prognosis. The objective of this study was to evaluate whether patient-reported baseline quality of life (QoL) measured by the EORTC QLQ-C30 instrument is predictive of survival for these patients.
Materials and methods: Two hundred and thirty-three patients with unresectable HCC (mainly hepatitis B-associated) who were recruited into two separate randomized phase III clinical studies, based on palliative chemotherapy and palliative hormonal therapy, respectively, gave consent and received pretreatment QoL assessment. EORTC QLQ-C30 scores and clinical variables at the time of study entry were analyzed to identify factors that influenced survival by applying multivariate analysis. Independent prognostic factors for survival were studied by Cox regression analysis.
Results: Median survival of the 233 patients was 5.5 months (95% CI 4.26.5 months). Significant independent predictors of shorter survival were advanced Okuda staging (P = 0.0030; HR = 2.058), high baseline total bilirubin (P = 0.0008; HR = 1.013) and worse QoL score in the appetite score domain (P = 0.0028; HR for 10 point increase = 1.070). Patients who were entered into the chemotherapy trial (P = 0.0002; HR = 0.503), those who scored better in the physical functioning domain (P = 0.0034; HR for 10 point decrease = 0.911) and the role functioning domain (P = 0.0383; HR for 10 point decrease = 0.944) of the QoL questionnaire, were associated with longer survival.
Conclusions: In the studied HCC population, patient-reported baseline QoL provides additional prognostic information that supplements traditional clinical factors, and is a new prognostic marker for survival for patients with unresectable HCC.
Key words: liver cancer, QoL, prognostic markers
| introduction |
|---|
|
|
|---|
Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and is one of the commonest causes of cancer morbidity and mortality in China and the Far East [1
Quality of life (QoL) is an important aspect of palliative care treatment. QoL has been acknowledged as an important end point in cancer clinical trials and clinical practice, along with the traditional end points including tumor response rate, disease-free survival and overall survival [13
, 14
]. More recently, pretreatment QoL has been increasingly recognized as a potential prognostic factor of survival [15
].
Several studies have investigated prognostic factors in patients with hepatocellular carcinoma and these have been reported to enable differentiation of patients with favorable and adverse prognosis [16
22
]. While some studies have undertaken analysis on early operable HCC [22
, 23
], others have included patients with various stages of HCC [16
21
]. Most prognostic systems including the Cancer of the Liver Italian Program (CLIP), Barcelona Clinic Liver Cancer (BCLC), and French and Central European systems are based on patient population associated mostly with hepatitis C infection and alcoholic liver disease [17
20
]. Prognostication based on those associated with chronic hepatitis B infection has mainly been addressed by the Chinese University Prognostic Index (CUPI) [21
]. However, to date, there are no studies that assessed whether baseline QoL provides prognostic information in addition to conventional clinical factors for patients with unresectable disease. Prediction of clinical outcome may enable risk stratification and aid proper assignment of appropriate therapeutic strategies to individual patients.
The aim of the present study was to evaluate whether patient-reported baseline QoL is predictive of survival for patients with unresectable HCC who were mainly associated with chronic hepatitis B infection.
| materials and methods |
|---|
|
|
|---|
The study population consisted of 233 patients from two phase III randomized studies for patients with unresectable HCC that were conducted during the same period in the Department of Clinical Oncology at Prince of Wales Hospital (Shatin, N.T., Hong Kong). One of the phase III randomized trials compared the efficacies and tolerability of two different palliative chemotherapeutic regimens: single-agent doxorubicin with combination cisplatin/interferon-
2b/doxorubicin/5-fluorouracil chemotherapy (hereby termed as the chemotherapy study) [24The protocols of both studies were approved by the Clinical Research Ethics Committee of the Chinese University of Hong Kong.
entry and exclusion criteria
Patients were eligible if they had confirmed unresectable or metastatic disease HCC with no prior systemic therapy. The diagnosis of HCC was confirmed by either histology (biopsy), or radiology (a space occupying lesion on liver ultrasonography) and a raised
-fetoprotein (AFP)
500 µg/l. Other entry criteria included: age <80 years, ECOG performance score between 0 and 2, adequate renal function (creatinine clearance >50 ml/min), no prior history of malignancy except skin cancer and presence of encephalopathy, no cognitive impairment (as judged by attending clinician) and an ability to understand and read Chinese.
treatment received
For the chemotherapy study, patients were randomized to receive either single-agent doxorubicin (60 mg/m2 on day 1 every 3 weeks) or PIAF (cisplatin 20 mg/m2 days 14, interferon-
2b 5 MU/m2 days 14, doxorubicin 40 mg/m2 day 1, 5-fluorouracil 400 mg/m2 days 14 every 3 weeks). The chemotherapy was administered for up to six cycles for responding disease and tolerable toxicities.
For the hormonal study, patients were randomized into one of the three groups, namely, placebo, tamoxifen 60 mg/day, or tamoxifen 120 mg/day in a ratio of 2:1:2. Treatment was continued for patients with tolerable toxicities.
qoL assessment
The Chinese version of the EORTC QLQ-C30 was used. After consent, all patients completed the questionnaire before the allocated treatment was commenced. The EORTC QLQ-C30 questionnaire is a widely used questionnaire. It incorporates a range of QoL issues relevant to a broad range of cancer patients. It has been translated into many languages and validated for many cancer types. It contains five functional scales (physical, role, cognitive, emotional and social), three symptom scales (fatigue, pain and nausea/vomiting), a global QoL scale and six single items (dyspnoea, insomnia, appetite loss, constipation, diarrhea and financial difficulties) [26
]. All scales and items of the EORTC QLQ-C30 range in score from 0 to 100. A high score for a functional or global QoL scale represents a relatively high/healthy level of functioning or global QoL, and a high score for a symptom scale or item represents a more severe symptoms or problems [27
].
prognostic clinical variables
The following conventional clinical prognostic variables were included as potential clinical covariates: age, sex, ECOG performance score, AFP, total bilirubin, alanine transaminase and albumin levels, prothrombin time, HBsAg seropositivity, presence of ascites, ChildPugh's grading of cirrhosis, vascular involvement, Okuda staging of HCC [16
], TNM staging of HCC [28
] and entries into the two respective studies (i.e. chemotherapy study versus hormonal study).
statistical analysis
Overall survival was measured from the day of randomization to the date of death or last contact. Both studies have their data updated for the final analysis and the frozen dataset were used for this analysis. Survival curves were estimated with the KaplanMeier method.
For the EORTC QLQ-C30 scores, all the five functioning domains, the global quality of life domain and the three symptom domains plus six single items related to symptoms were included in the prognostic factor analysis as continuous variables. They were transformed into a scale range from 0 to 100. EORTC QLQ-C30 scores and conventional clinical variables at the time of entry to the two respective studies were analyzed to identify factors that influenced survival by Cox proportional hazards model. Multivariate analysis was also carried out using a stepwise model building procedure based on a significance value of 0.05 for both inclusion and exclusion of prognostic factors. The statistical analysis was performed using SAS version 8 software package.
| results |
|---|
|
|
|---|
study population
Two hundred and thirty-three patients with unresectable HCC were entered into the present study. These included 156 consecutive patients (67%) from the chemotherapy study and 77 consecutive patients (33%) from the hormonal study. Table 1 illustrates the baseline characteristics of the 233 patients in the present study. The median age of the patients was 57 years (range 1680). Two hundred and twelve were males (91%). Eighty per cent of patients had an ECOG performance score of 0. Eighty-four per cent were HBsAg positive. The median AFP level was 3267 IU/l (range 11 892 600); that of the others were: albumin 33 g/l (range 446), total bilirubin 14 µmol/l (range 4206), alanine transaminase 65 IU/l (range 13346) and prothrombin time 11.6 s (range 9.224.9). Nineteen per cent had ascites. Sixty-nine per cent had ChildPugh's grade A, 27% were of grade B and 4% were of grade C. Forty-nine per cent had vascular involvement. Most patients had extensive tumor involvement as classified by the Okuda staging: 7% were stage I, 80% stage II and 13% stage III. According to TNM staging, 12% were stage I and II, 17% were stage IIIA and IIIB, 54% were stage IVA and 17% were stage IVB.
|
Table 2 illustrates the details of the two patient subgroups (from the chemotherapy study and the hormonal study) from the present study together with the baseline characteristics of the overall chemotherapy and hormonal trial populations. The two subgroups of patients who were recruited into the present study had similar baseline characteristics as that of the overall patient populations in the two respective trials.
|
Two hundred and nine (90%) patients had died; these included 134 from the chemotherapy study and 75 from the hormonal study. The median survival of the 233 patients was 5.5 months (95% CI 4.26.5 months).
univariate analysis
Univariate analysis on the prognostic significance of the clinical predictors of survival are listed in Table 1. Variables that were statistically significant predictors of a shorter survival time included advanced Okuda staging (III versus I + II), presence of ascites, poor ECOG performance score (>0), and high AFP, total bilirubin and alanine transaminase levels. Variables that were statistically significant predictors of a longer survival time included early cirrhosis (ChildPugh's grade), high albumin level and having been recruited to the treatment in the chemotherapy study. Age, gender, HBsAg seropositivity and prothrombin time were not significantly predictive.
Table 3 lists the univariate analysis of the predictive significance of QoL variables. A better score in physical functioning, role functioning, cognitive functioning, social functioning and global quality of life were significantly related to longer survival. While a worse score in fatigue, nausea, pain, appetite and constipation were significantly associated with shorter survival (P < 0.05). Emotional functioning, nausea/vomiting, dyspnoea, insomnia, diarrhea and financial difficulties were not significantly predictive.
|
multivariate analysis
Multivariate analysis was performed to investigate the prognostic effect of QoL variables and the clinical variables simultaneously. The results are listed in Table 4. Significant independent predictors of shorter survival were advanced Okuda staging (P = 0.0030; HR = 2.058, 95% CI 1.2783.315), high baseline total bilirubin (P = 0.0008; HR = 1.013, 95% CI 1.0051.020) and worse score in the appetite scale of the QOL questionnaire. For a 10-point increase in score for appetite loss there was a 7% increase in the likelihood of death at any given time (P = 0.0028, HR = 1.070, 95% CI 1.0231.118).
|
Patients who were entered into the chemotherapy study (P = 0.0002; HR = 0.503, 95% CI, 0.3520.721), those who scored better in the physical functioning domain and the role functioning domain of the QoL questionnaire were associated with longer survival. For a 10-point increase in physical functioning score there was an 8.9% reduction in the likelihood of death at any given time (P = 0.0034, HR = 0.911, 95% CI 0.8560.969). For a 10-point increase in role functioning score there was a 5.6% reduction in the likelihood of death at any given time (P = 0.0383, HR = 0.944; 95% CI 0.8940.996). Figure 1 shows the survival curves of patients according to different scores of physical functioning, role functioning and appetite loss. The cut-off points for physical functioning, role functioning and appetite loss were 70, 70 and 25, respectively. The determination of these cut-off points were based on the mean value score observed in the study patient population. For each figure, the difference between the two curves was significant (P = 0.0005, 0.0033 and <0.0001, respectively).
|
The study by QoL interaction was tested; results were similar between the two study groups (P = 0.7508).
| conclusions |
|---|
|
|
|---|
To our knowledge, our study is the first retrospective analysis of two prospective studies in patients with unresectable hepatocellular carcinoma to confirm the prognostic significance of QoL in a fairly homogenous group of patients. The findings provide strong evidence to support a relationship between QoL scores and survival in this patient population, in which the majority suffered from chronic liver disease associated with hepatitis B infection. Several baseline predictors of survival were found upon multivariate Cox analysis, in particular, a major finding was that baseline EORTC QLQ-C30 scores in physical functioning, role functioning and appetite loss were significantly associated with survival and, therefore, have predictive value when used along with the current standard clinical prognostic variables.
Individuals who have worse baseline QoL scores were found to have shorter survival than those who have better QoL scores. While this relationship has not been universally observed in the literature, such positive correlation has been reported in a number of cancer types [29
32
], specifically, in the breast [33
35
], lung [36
39
], esophagus [40
42
], head and neck [43
], colon [44
], malignant melanoma [45
], multiple myeloma [46
], ovarian [47
] and malignant glioma [48
]. However, different QOL instruments have been used in these studies, and it may be difficult to generalize the findings. Using EORTC QLQ-C30 as a tool of assessment, global QoL [29
, 30
, 32
, 36
, 37
, 42
] and physical functioning [30
, 31
, 40
, 41
, 46
] have been the most common domains that were shown to be predictors of survival. Other aspects that have been shown to be of prognostic significance include emotional functioning [29
], social functioning [32
], role functioning [42
], cognitive functioning [43
], pain [34
] and appetite loss [35
]. In HCC patients, appetite loss may be a reflection of the disease burden and severity of the often associated chronic liver disease; a large-sized tumor is likely to compress adjacent stomach, the presence of gross ascites may cause a feeling of abdominal fullness, hepatic dysfunction with hyperbilirubinemia may reduce mental state and impair appetite, and the reduction of body reserve as a consequence may lead to poor tolerance to intervention therapy and result in premature termination of the treatment.
The predictive value of baseline QoL for survival is probably due to the ability to provide information about patient well-being not captured by traditional measures. It is a patient-reported assessment of well-being. Historically, clinical observers have been reported to be poor judges of how a patient feels. Low correlations are found between patient-reported and clinician-reported overall QoL scores, symptoms, physical well-being and psychological well-being subscores [49
, 50
].
The present study was undertaken to explore further the relationship of baseline QoL with conventional clinical covariates and survival in patients with inoperable HCC. Advanced disease based on Okuda staging and high total bilirubin were two covariates strongly associated with shorter survival. These findings are incongruent with previous reports in which patients with various stages of HCC were studied by applying different prognostic systems [16
, 18
21
]. Tumor-related factors that have been predictive for survival include tumor size [16
, 17
, 21
], lymph node involvement [19
, 21
], presence of vascular thrombosis or invasion [17
20
] and high AFP levels [18
, 19
, 21
]. Functional status of the non-tumorous liver, as reflected by adequacy of liver function, has also been widely accepted to have prognostic significance. Apart from high total bilirubin [16
, 18
21
], low albumin [16
], high alkaline phosphatase [18
, 21
], presence of ascites [16
, 21
] or portal hypertension [20
], prolonged prothrombin time [19
] and advanced ChildPugh stage for cirrhosis [17
, 20
] have been shown to be adverse prognostic factors for survival in HCC patients. Furthermore, in the absence of formal QoL assessment, patients who are asymptomatic at presentation of the disease [21
] and those who have good performance status [18
] have been associated with better outcome.
The other factor that predicted survival was the treatment an individual received, with patients receiving chemotherapy having a longer survival. The exact causal relationship was unclear. While it may be consideredchemotherapy represents a more aggressive approach in the management of HCC, which could theoretically result in a better outcome for the patients treatedit was likely that those who had more favorable baseline clinical features were more likely to be selected for chemotherapy. However, it is unlikely that treatment effect would impact on the analysis of prognostic factors since the two studies have negative results [24
, 25
]. This is supported by a subsequent exploratory analysis testing the study-by-QoL interactions, which did not show any significant difference between the two treatment groups.
It is possible that baseline QoL for HCC patients may be affected by other concurrent diseases or conditions. In the context of assessing treatment outcome of patients with cancer of the liver, pancreas, gall bladder and biliary ducts, addressing disease-specific issues has been acknowledged to be an important component of quality of life assessment. The Functional Assessment of Cancer Therapy hepatobiliary questionnaire (FACT-Hep) supplements the general quality of life questionnaire (FACT-G), and has been used as a tool for assessing treatment outcome for patients with hepatobiliary malignancies [51
]. FACT-Hep has been put forth as a reliable and valid instrument that increases the accuracy of overall QoL assessment [51
]. Specifically, for patients with hepatocellular carcinoma, with the majority of patients suffering from co-existing cirrhosis, the usefulness of a QoL instrument based on EORTC QLQ-C30 in assessing patients with HCC could be further enhanced by the addition of assessment related to disease-specific module in the recently reported EORTC QLQ-HCC18 questionnaire [52
]. In the latter, symptoms from chronic liver disease have been taken into consideration and include that of abdominal distension from ascites, limb edema related to sodium and fluid retention, pruritus related to hyperbilirubinemia, bleeding related to clotting impairment and thrombocytopenia [52
]. The inclusion of a HCC-specific questionnaire into the present study would potentially improve the sensitivity of baseline QoL as a prognosticator in these patients.
Our study suggests that baseline QoL as measured by EORTC QLQ-C30 could be applied as a new prognostic marker for survival in patients with unresectable hepatocellular carcinoma. When used together with conventional clinical factors, patient-reported baseline QoL assessment provides additional information and can be part of a more comprehensive prediction of patient prognosis. Furthermore, QoL assessment enables identification of symptoms whereby interventions to improve QoL may be useful in reducing the burden of the disease. QoL assessment may also assist clinicians to recalibrate clinical prediction of survival and optimize the use of palliative care. From a clinical research perspective, the identification of prognostic factors for survival could help to stratify patients into randomized clinical trials and aid the interpretation of results in a more transparent way.
The findings from this study support the use of QoL assessment in being informative in routine clinical practice in a HCC patient population with background chronic liver disease mainly associated with hepatitis B infection. Although the data was prospectively collected, the findings are limited by the retrospective nature of data analysis. Further studies incorporating QoL assessment together with clinical prognostic systems may provide additional information that may aid patient and clinician in decision-making in unresectable hepatocellular carcinoma.
| Acknowledgements |
|---|
We thank Asia Pacific Hepatocellular Carcinoma Trials Group for providing QOL data for patients who consented to the randomized trial of high-dose tamoxifen versus placebo for the treatment of inoperable hepatocellular carcinoma.
Received for publication November 28, 2005. Revision received February 14, 2006. Accepted for publication February 28, 2006.
| References |
|---|
|
|
|---|
1. Bosch FX, Ribes J, Diaz M, Cleries R. Primary liver cancer: worldwide incidence and trends. Gastroenterology 2004; 127 (5 Suppl 1): S5S16.[CrossRef][Web of Science][Medline]
2. Cancer incidence and mortality in Hong Kong 19992000. Hong Kong Cancer Registry, Hospital Authority 2004.
3. Ho J, Wu PC, Kung TM. An autopsy study of hepatocellular carcinoma in Hong Kong. Pathology 1981; 13: 409416.[Web of Science][Medline]
4. Lok ASF, Lai CL, Wu PC et al. Hepatitis B virus infection in Chinese families in Hong Kong. Am J Epidemiol 1987; 126: 492499.
5. Pawarode A, Voravud N, Sriuranpong V et al. Natural history of untreated primary hepatocellular carcinoma: a retrospective study of 157 patients. Am J Clin Oncol 1998; 21: 386391.[CrossRef][Web of Science][Medline]
6. Calvet X, Bruix J, Gines P et al. Prognostic factors of hepatocellular carcinoma in the west: a multivariate analysis in 206 patients. Hepatology 1990; 12: 753760.[Web of Science][Medline]
7. Okuda K. Primary liver cancers in Japan. Cancer 1980; 45: 26632672.[CrossRef][Web of Science][Medline]
8. Lai EC, Fan ST, Lo CM et al. Hepatic resection for hepatocellular carcinoma. An audit of 343 patients. Ann Surg 1995; 221: 291298.[Web of Science][Medline]
9. Johnson PJ. Hepatocellular carcinoma: is current therapy really altering outcome? Gut 2002; 51: 459462.
10. Leung TW, Johnson PJ. Systemic therapy for hepatocellular carcinoma. Semin Oncol 2001; 28: 514520.[CrossRef][Web of Science][Medline]
11. Simonetti RG, Liberati A, Angiolini C, Pagliaro L. Treatment of hepatocellular carcinoma: A systemic review of randomized controlled trials. Ann Oncol 1997; 8: 117136.
12. CLIP Group. Tamoxifen in treatment of hepatocellular carcinoma: a randomised controlled trial. Lancet 1998; 352: 1720.[CrossRef][Medline]
13. Editorial. Quality of life and clinical trials. Lancet 1995; 346: 12.[Web of Science][Medline]
14. Moinpour CM. Measuring quality of life: an emerging science. Sem Oncol 1994; 21 (Suppl 10): 4863.[Medline]
15. Danzey J, Zee B, Osaba D et al. Quality of life scores: an independent prognostic variable in a general population of cancer patients receiving chemotherapy. The National Cancer Institute of Canada Clinical trials Group. Qual Life Res 1997; 6: 151158.[Web of Science][Medline]
16. Okuda K, Ohtsuki T, Obata H et al. Natural history of hepatocellular carcinoma and prognosis in relation to treatment. Study of 850 patients. Cancer 1985; 56: 918928.[CrossRef][Web of Science][Medline]
17. The Cancer of the Liver Italian Program (CLIP) Investigators: a new prognostic system for hepatocellula carcinoma. Hepatology 1998; 28: 751755.[CrossRef][Web of Science][Medline]
18. Chevret S, Trinchet JC, Mathieu D et al. A new prognostic classification for predicting survival in patients with hepatocellular carcinoma. Groupe d'Etude et de Traitement du Carcinome Hepatocellulaire. J Hepatol 1999; 31: 133141.[CrossRef][Medline]
19. Schoniger-Hekele M, Muller C, Kutilek M et al. Hepatocellular carcinoma in Central Europe: prognostic features and survival. Gut 2001; 48: 103109.[Medline]
20. Llovet JM, Bru C, Bruix J. Prognosis of hepatocellular carcinoma: the BCLC staging classification. Semin Liver Dis 1999; 19: 329338.[Medline]
21. Leung T, Tang A, Zee B. Construction of the Chinese University Prognostic Index for hepatocellular carcinoma and comparison with TNM staging system, the Okuda staging system, and the Cancer of the Liver Italian Program staging system. Cancer 2002; 94: 17601769.[CrossRef][Medline]
22. Vauthey J-N, Lauwers GY, Esnaola NF et al. Simplified staging for hepatocellular carcinoma. J Clin Oncol 2002; 20: 15271536.
23. Tateishi R, Yoshida H, Shiina S. Proposal of a new prognostic model for hepatocellular carcinoma: an analysis of 403 patients. Gut 2005; 54: 419425.
24. Yeo W, Zee B, Leung WT et al. A phase III study of adriamycin (A) versus cisplatin (P)/interferon
-2b (I)/adriamycin (A)/fluorouracil (F) combination chemotherapy (PIAF) for inoperable hepatocellular carcinoma (HCC). Proc Am Soc Clin Oncol 2004; 23: 319.
25. Chow PKH, Tai BC, Tan CK et al. High dose tamoxifen in the treatment of inoperable hepatocellular carcinoma: a multicenter randomized controlled trial. Hepatology 2002; 36: 12211226.[CrossRef][Web of Science][Medline]
26. Aaronson NK, Ahmedzai Bergman B et al. The European Organization of Research and Treatment of Cancer QLQ-C30: a quality of life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993; 85: 365376.
27. Fayers P, Aaronson NK, Bjordal K et al. EORTC QLQ-C30 Scoring Manual, 2nd edition. Belgium: EORTC Data Center 1999.
28. Sobin LH, Wittekind C (eds). TNM Classification of Malignant Tumors, 5th edition. Union Internationale Centre le Cancer. New York: John Wiley & Sons 1997.
29. Dancey J, Zee B, Osoba D et al. for the National Cancer Institute of Canada Clinical Trials Group. Quality of life scores: an independent prognostic variable in a general population of cancer patients receiving chemotherapy. Qual Life Res 1997; 6: 151158.[Web of Science][Medline]
30. Ringdal GI, Ringdal K, Kvinnsland S et al. Quality of life of cancer patients with different prognosis. Qual Life Res 1994; 3: 143154.[CrossRef][Medline]
31. Ringdal GI, Gotestam KG, Kaasa S et al. Prognostic factors and survival in a heterogeneous sample of cancer patients. Br J Cancer 1996; 73: 15941599.[Web of Science][Medline]
32. Coates A, Porzsolt F, Osoba D. Quality of life in oncology practice: Prognostic value of EORTC QLQ-C30 scores in patients with advanced malignancy. Eur J Cancer 1997; 33: 10251030.[CrossRef][Web of Science][Medline]
33. Coates A, Forbes J, Simes RJ. Prognostic value of performance status and quality of life scores during chemotherapy for advanced breast cancer. The Australian New Zealand Breast Cancer Trials Group. J Clin Onol 1993; 11: 2050.[Medline]
34. Kramer JA, Curran D, Piccart M et al. Identification and interpretation of clinical and quality of life prognostic factors for survival and response to treatment in first-line chemotherapy in advanced breast cancer. Eur J Cancer 2000; 36: 14981506.[CrossRef][Web of Science][Medline]
35. Efficace F, Biganzoli L, Piccart M et al. Baseline health-related quality of life data as prognostic factors in a phase III multicentre study of women with metastatic breast cancer. Eur J Cancer 2004; 40: 10211030.[Medline]
36. Langendijk H, Aaronson NK, de Jong JMA et al. The prognostic impact of quality of life assessed with the EORTC QLQ-C30 in inoperable non-small cell lung carcinoma treated with radiotherapy. Radiother Oncol 2000; 55: 1925.[CrossRef][Web of Science][Medline]
37. Montazeri A, Milroy R, Hole D et al. Quality of life in lung cancer patients as an important prognostic factor. Lung Cancer 2001; 31: 233240.[CrossRef][Web of Science][Medline]
38. Herndon JE, Fleishman S, Kornblith AN et al. Is quality of life predictive of the survival of patients with advanced nonsmall cell lung carcinoma? Cancer 1999; 85: 333340.[CrossRef][Web of Science][Medline]
39. Dharma-Wardene M, Au HJ, Hanson J et al. Baseline FACT-G score is a predictor of survival for advanced lung cancer. Quality of Life Reseach 2004; 13: 12091216.
40. Blazeby JM, Brookes ST, Alderson D. The prognostic value of quality of life scores during treatment for oesophageal cancer. Gut 2001; 49: 227230.
41. Fang FM, Tsai WL, Chiu H et al. Quality of life as a survival predictor for esophageal squamous cell carcinoma treated with radiotherapy. Int J Radiation Biol Phys 2004; 58: 13941404.[CrossRef]
42. Chau I, Norman AR, Cunningham D et al. Multivariate prognostic factor analysis in locally advanced and metastatic esophago-gastric cancer-pooled analysis from three multicenter, randomized, controlled trails using individual patients Data. J Clin Oncol 2004; 22: 23952403.
43. de Graeff A, de Leeuw JRJ, Ros WJG et al. Sociodemographic factors and quality of life as prognostic indicators in head and neck cancer. Eur J Cancer 2001; 37: 332339.[CrossRef][Medline]
44. Ramsey SD, Anderson MR, Etzioni R et al. Quality of life in survivors of colorectal carcinoma. Cancer 2000; 39: 12941303.
45. Coates A, Thomson D, McLeod GR et al. Prognostic value of quality of life scores in a trial of chemotherapy with or without interferon in patients with metastatic malignant melanoma. Eur J Cancer 1993; 29A: 17311734.
46. Wisloff F, Hjorth M et al for the Nordic Myeloma Study Group. Health-related quality of life assessed before and during chemotherapy predicts for survival in multiple myeloma. Br J Haematol 1997; 97: 2937.[Medline]
47. Kornblith AB, Thaler HT, Wong G et al. Quality of life of women with ovarian cancer. Gynecol Oncol 1995; 59: 231242.[CrossRef][Medline]
48. Langendijk H, Aaronson NK, ten Velde GP et al. Pretreatment quality of life in patients with gIioblastoma multiforme. Oncol Nurs Forum 1999; 26: 921925.[Medline]
49. Blazeby JM, Williams MH, Alderson D, Farndon JR. Observer variation in assessment of quality of life in patients with oesophageal cancer. Br J Surg 1995; 82: 12001203.[Web of Science][Medline]
50. Wilson KA, Dowling AJ, Abdolell M, Tannock IF. Perception of quality of life by patients, partners and treating physicians. Qual Life Res 2000; 9: 10411052.[CrossRef][Web of Science][Medline]
51. Heffernan N, Cella D, Webster K et al. Measuring health-related quality of life in patients with hepatobiliary cancers: the functional assessment of cancer therapy-hepatobiliary questionnaire. Clin Oncol 2002; 20: 22292239.
52. Blazeby JM, Currie E, Zee BC et al. Development of a questionnaire module to supplement the EORTC QLQ-C30 to assess quality of life in patients with hepatocellular carcinoma, the EORTC QLQ-HCC18. Eur J Cancer 2004; 40: 24392444.[Medline]
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
E. Basch, X. Jia, G. Heller, A. Barz, L. Sit, M. Fruscione, M. Appawu, A. Iasonos, T. Atkinson, S. Goldfarb, et al. Adverse Symptom Event Reporting by Patients vs Clinicians: Relationships With Clinical Outcomes J Natl Cancer Inst, November 17, 2009; (2009) djp386v1. [Abstract] [Full Text] [PDF] |
||||
![]() |
G. Spinzi, S. Paggi, M. S. Copur, D. H. Palmer, J. M. Llovet, J. Bruix, and L. R. Roberts Sorafenib in Advanced Hepatocellular Carcinoma N. Engl. J. Med., December 4, 2008; 359(23): 2497 - 2499. [Full Text] [PDF] |
||||
![]() |
S. Collette, F. Bonnetain, X. Paoletti, M. Doffoel, O. Bouche, J. L. Raoul, P. Rougier, F. Masskouri, L. Bedenne, and J. C. Barbare Prognosis of advanced hepatocellular carcinoma: comparison of three staging systems in two French clinical trials Ann. Onc., June 1, 2008; 19(6): 1117 - 1126. [Abstract] [Full Text] [PDF] |
||||
![]() |
F. Efficace, P. F. Innominato, G. Bjarnason, C. Coens, Y. Humblet, S. Tumolo, D. Genet, M. Tampellini, A. Bottomley, C. Garufi, et al. Validation of Patient's Self-Reported Social Functioning As an Independent Prognostic Factor for Survival in Metastatic Colorectal Cancer Patients: Results of an International Study by the Chronotherapy Group of the European Organisation for Research and Treatment of Cancer J. Clin. Oncol., April 20, 2008; 26(12): 2020 - 2026. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. C. Gotay, C. T. Kawamoto, A. Bottomley, and F. Efficace The Prognostic Significance of Patient-Reported Outcomes in Cancer Clinical Trials J. Clin. Oncol., March 10, 2008; 26(8): 1355 - 1363. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

70, lower curve) (n = 233, log-rank test: P value = 0.0005). (B) Survival (months) of patients with optimal role functioning (score >70, upper curve) versus survival of patients with less than optimal global QOL (score 


