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Interpretation and review of health-related quality of life data in CKD patients receiving treatment for anemia

2008; Elsevier BV; Volume: 75; Issue: 1 Linguagem: Inglês

10.1038/ki.2008.414

1523-1755

David E. Leaf, David S. Goldfarb,

Hemoglobinopathies and Related Disorders

Recent evidence suggests that targeting higher hemoglobin values with erythropoiesis stimulating agents (ESAs) may lack mortality benefits and may even result in adverse cardiovascular complications when used in chronic kidney disease patients. However, ESAs are frequently reported to result in improvements in health-related quality of life (HRQOL). The purpose of this review is to evaluate the magnitude and nature of ESA-associated improvements in HRQOL, as well as to understand how to interpret the clinical significance of HRQOL data. HRQOL findings should be analyzed not by statistical significance but rather by using a minimal clinically important difference approach, or, alternatively, a distribution-based approach (such as Cohen's effect size). HRQOL domains that are most improved with ESAs relate to physical symptoms, vitality, energy, and performance; domains of social functioning and mental health show modest improvement, whereas the domains of emotional functioning and pain show very little improvement. Additional domains not measured by commonly used instruments (such as the SF-36) that have been shown to improve with ESAs include sleep, cognitive functioning, and sexual functioning. The maximal increase in HRQOL per incremental increase in hemoglobin appears to occur in the range of 10–12 g/dl. Beyond this range, additional normalization of hemoglobin (to 12–14 g/dl) results in continued (albeit blunted) improvements in HRQOL. Recent evidence suggests that targeting higher hemoglobin values with erythropoiesis stimulating agents (ESAs) may lack mortality benefits and may even result in adverse cardiovascular complications when used in chronic kidney disease patients. However, ESAs are frequently reported to result in improvements in health-related quality of life (HRQOL). The purpose of this review is to evaluate the magnitude and nature of ESA-associated improvements in HRQOL, as well as to understand how to interpret the clinical significance of HRQOL data. HRQOL findings should be analyzed not by statistical significance but rather by using a minimal clinically important difference approach, or, alternatively, a distribution-based approach (such as Cohen's effect size). HRQOL domains that are most improved with ESAs relate to physical symptoms, vitality, energy, and performance; domains of social functioning and mental health show modest improvement, whereas the domains of emotional functioning and pain show very little improvement. Additional domains not measured by commonly used instruments (such as the SF-36) that have been shown to improve with ESAs include sleep, cognitive functioning, and sexual functioning. The maximal increase in HRQOL per incremental increase in hemoglobin appears to occur in the range of 10–12 g/dl. Beyond this range, additional normalization of hemoglobin (to 12–14 g/dl) results in continued (albeit blunted) improvements in HRQOL. Given recent trials demonstrating that complete compared with partial correction of anemia in chronic kidney disease (CKD) patients does not appear to reduce the risk of cardiovascular complications1.Drueke T.B. Locatelli F. Clyne N. et al.Normalization of hemoglobin level in patients with chronic kidney disease and anemia.N Engl J Med. 2006; 355: 2071-2084Crossref PubMed Scopus (1674) Google Scholar and may even contribute to an increased propensity for adverse complications,2.Singh A.K. Szczech L. Tang K.L. et al.Correction of anemia with epoetin alfa in chronic kidney disease.N Engl J Med. 2006; 355: 2085-2098Crossref PubMed Scopus (2129) Google Scholar the benefits of erythropoiesis-stimulating agents (ESAs) are being debated. An improvement in health-related quality of life (HRQOL) is frequently cited as an effect of successful treatment of anemia. We therefore sought to understand and review the magnitude and nature of ESA-associated improvements in HRQOL. The National Kidney Foundation defines anemia as a hemoglobin (Hb) concentration less than 12.0 g/100 ml in women and less than 13.5 g/100 ml in men.3.KDOQI; National Kidney Foundation KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Anemia in Chronic Kidney Disease.Am J Kidney Dis. 2006; 47: S11-S145Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar Despite the availability of recombinant human erythropoietin since 1989, the treatment of anemia in patients with CKD and cancer remains an enormous burden to the health care system.4.Smith D.H. Gullion C.M. Nichols G. et al.Cost of medical care for chronic kidney disease and comorbidity among enrollees in a large HMO population.J Am Soc Nephrol. 2004; 15: 1300-1306Crossref PubMed Scopus (156) Google Scholar For example, the point prevalence of anemia associated with CKD in the United States is estimated to be four million people.5.McClellan W. Aronoff S.L. Bolton W.K. et al.The prevalence of anemia in patients with chronic kidney disease.Curr Med Res Opin. 2004; 20: 1501-1510Crossref PubMed Scopus (316) Google Scholar Anemia is associated with cardiovascular complications such as worsening heart failure, left ventricular hypertrophy, and angina.6.Muzzarelli S. Pfisterer M. Anemia as independent predictor of major events in elderly patients with chronic angina.Am Heart J. 2006; 152: 991-996Abstract Full Text Full Text PDF PubMed Scopus (62) Google Scholar It has also been associated with functional impairment, mobility impairment, increased risk of falls, and diminished HRQOL.7.Kamenetz Y. Beloosesky Y. Zeltzer C. et al.Relationship between routine hematological parameters, serum IL-3, IL-6 and erythropoietin and mild anemia and degree of function in the elderly.Aging (Milano). 1998; 10: 32-38PubMed Google Scholar, 8.Dharmarajan T.S. Norkus E.P. Mild anemia and the risk of falls in older adults from nursing homes and the community.J Am Med Dir Assoc. 2004; 5: 395-400Abstract Full Text Full Text PDF PubMed Scopus (63) Google Scholar, 9.Cella D. The Functional Assessment of Cancer Therapy-Anemia (FACT-An) Scale: a new tool for the assessment of outcomes in cancer anemia and fatigue.Semin Hematol. 1997; 34: 13-19PubMed Google Scholar, 10.Glaspy J. Bukowski R. Steinberg D. et al.Impact of therapy with epoetin alfa on clinical outcomes in patients with nonmyeloid malignancies during cancer chemotherapy in community oncology practice. Procrit Study Group.J Clin Oncol. 1997; 15: 1218-1234PubMed Google Scholar Treatment of anemia using ESAs has consistently improved HRQOL, as demonstrated by several meta-analyses.11.Ross S.D. Fahrbach K. Frame D. et al.The effect of anemia treatment on selected health-related quality-of-life domains: a systematic review.Clin Ther. 2003; 25: 1786-1805Abstract Full Text PDF PubMed Scopus (91) Google Scholar, 12.Strippoli G.F. Navaneethan S.D. Craig J.C. Haemoglobin and haematocrit targets for the anaemia of chronic kidney disease.Cochrane Database of Systematic Reviews. 2006Crossref Google Scholar However, the measurement of HRQOL is fraught with difficulties, as neither a universal nor a gold standard instrument has been adopted for the quantification of this necessarily subjective entity.13.Cella D.F. Methods and problems in measuring quality of life.Support Care Cancer. 1995; 3: 11-22Crossref PubMed Scopus (59) Google Scholar Moreover, when attempts are made to quantify improvements in HRQOL, such improvements are often described as mean changes in the score of a standardized instrument instead of in language with which clinicians and patients are more familiar. Finally, in discussing ESA therapy, the cost of improving HRQOL is often not mentioned, though it is very significant, measured as billions of dollars.14.Coladonato J.A. Frankenfield D.L. Reddan D.N. et al.Trends in anemia management among US hemodialysis patients.J Am Soc Nephrol. 2002; 13: 1288-1295Crossref PubMed Scopus (64) Google Scholar Questions that will be addressed in this review include the following: (1) what are the most commonly used instruments used in the measurement of HRQOL in CKD patients? (2) how does one interpret whether an improvement in an HRQOL score is clinically meaningful? (3) which domains and dimensions of HRQOL are most improved by treatment of anemia? (4) what is the magnitude of such improvements? and (5) what is the nature of improvements in HRQOL seen at different levels of Hb correction? The following is a brief description of some of the more commonly used measures of HRQOL. The Medical Outcomes Study Short Form-36 (SF-36) is a self-administered general health survey composed of 36 questions spanning eight physical and mental health domains (Figure 1).16.Stewart A.L. Hays R.D. Ware Jr, J.E. The MOS short-form general health survey. Reliability and validity in a patient population.Med Care. 1988; 26: 724-735Crossref PubMed Scopus (2904) Google Scholar Scores for the eight domains (or scales) are calculated from a subset of the 36 questions that pertain to that specific domain. For example, the vitality domain is computed based on the responses to four questions: 'how much of the time during the past 4 weeks did you feel (1) full of pep? (2) tired? (3) worn out? (4) full of energy?' Responses range from dichotomous answers to a maximum of six possible choices, with each choice being numerically coded and translated into a score, with higher scores indicating better health status. In addition, two summary measures can be computed as aggregates from four scales (Figure 1). The Sickness Impact Profile (SIP) is a self-administered behavior-based questionnaire that measures dysfunction related to illness.17.Bergner M. Bobbitt R.A. Carter W.B. et al.The Sickness Impact Profile: development and final revision of a health status measure.Med Care. 1981; 19: 787-805Crossref PubMed Scopus (3727) Google Scholar The complete instrument contains 136 items grouped into 12 domains: sleep and rest, emotional behavior, body care and movement, home management, mobility, social interaction, ambulation, alertness behavior, communication, work, eating, and recreation and pastimes. Multiple domains can be aggregated to give a physical dimension score and a psychosocial dimension score. An overall score can also be derived from the combined weighted scores of all 12 categories. Unlike the SF-36, higher scores on the SIP indicate greater disability. The Linear Analog Self-Assessment (LASA) scale, also known as the Visual Analog Scale, uses a 100 mm line with descriptors at each extreme, such as 'worst possible' and 'best possible' at the left and right ends of the scale, respectively. Subjects indicate their current state by making a mark somewhere along the line, which is then measured as a score in millimeters from the '0' point.13.Cella D.F. Methods and problems in measuring quality of life.Support Care Cancer. 1995; 3: 11-22Crossref PubMed Scopus (59) Google Scholar The LASA instrument includes 25 items encompassing the domains of physical functioning, symptoms and side effects, mood, energy, activity, overall QOL, and social relationships.18.Baum M. Priestman T. West R.R. et al.A comparison of subjective responses in a trial comparing endocrine with cytotoxic treatment in advanced carcinoma of the breast.Eur J Cancer. 1980: 223-226Google Scholar The Kidney Disease Questionnaire (KDQ) is specific for patients with end-stage renal disease and consists of 26 self-administered questions in five domains (physical symptoms, fatigue, depression, relationships with others, and frustration).19.Laupacis A. Muirhead N. Keown P. et al.A disease-specific questionnaire for assessing quality of life in patients on hemodialysis.Nephron. 1992; 60: 302-306Crossref PubMed Scopus (150) Google Scholar KDQ Part 1 asks patients to select the 6 most troublesome physical symptoms at baseline from a list of 30, and those symptoms are then used for that patient throughout the duration of a study. KDQ Part 2 asks patients about the remaining four domains. All questions are scored on a seven-point Likert scale (1=severe problem, 7=no problem) and domain scores (also ranging from 1 to 7) are calculated from a subset of corresponding questions. An overall score can be calculated as the sum of all KDQ domain scores. One of the most important and difficult challenges in studying HRQOL is translating apparent improvements in quality of life scores into clinically meaningful terms.20.Crosby R.D. Kolotkin R.L. Williams G.R. Defining clinically meaningful change in health-related quality of life.J Clin Epidemiol. 2003; 56: 395-407Abstract Full Text Full Text PDF PubMed Scopus (854) Google Scholar Because HRQOL scores are measured as continuous variables, improvements in such scores may be statistically significant and yet have little clinical relevance.13.Cella D.F. Methods and problems in measuring quality of life.Support Care Cancer. 1995; 3: 11-22Crossref PubMed Scopus (59) Google Scholar To aid clinicians and researchers in understanding the importance of changes in HRQOL scores, two tools are used with increasing frequency: the minimal clinically important difference (MCID) and the effect size. The MCID is most often defined as 'the smallest difference in score in the domain of interest which patients perceive as beneficial and which would mandate, in the absence of troublesome side effects and excessive cost, a change in the patient's management.'21.Jaeschke R. Singer J. Guyatt G.H. Measurement of health status. Ascertaining the minimal clinically important difference.Control Clin Trials. 1989; 10: 407-415Abstract Full Text PDF PubMed Scopus (3069) Google Scholar Some estimates of MCIDs for the four instruments described above are shown in Table 1. Although these estimates were not obtained from CKD patients specifically, Osoba and King28.Osoba D. King M. Interpreting QOL in individuals and groups: meaningful differences.in: Fayers P.H.R. Assessing Quality of Life in Clinical Trials: Methods and Practice. 2nd edn,. Oxford University Press, 2005: 243-257Google Scholar note a 'remarkable convergence of results' in HRQOL assessments among a diverse range of diseases, including asthma,29.Juniper E.F. Guyatt G.H. Willan A. et al.Determining a minimal important change in a disease-specific quality of life questionnaire.J Clin Epidemiol. 1994; 47: 81-87Abstract Full Text PDF PubMed Scopus (1475) Google Scholar chronic heart and lung disease,21.Jaeschke R. Singer J. Guyatt G.H. Measurement of health status. Ascertaining the minimal clinically important difference.Control Clin Trials. 1989; 10: 407-415Abstract Full Text PDF PubMed Scopus (3069) Google Scholar osteoarthritis,30.Ehrich E.W. Davies G.M. Watson D.J. et al.Minimal perceptible clinical improvement with the Western Ontario and McMaster Universities osteoarthritis index questionnaire and global assessments in patients with osteoarthritis.J Rheumatol. 2000; 27: 2635-2641PubMed Google Scholar and cancer.31.Osoba D. Rodrigues G. Myles J. et al.Interpreting the significance of changes in health-related quality-of-life scores.J Clin Oncol. 1998; 16: 139-144PubMed Google Scholar Similarly, Norman et al.32.Norman G.R. Sloan J.A. Wyrwich K.W. Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation.Med Care. 2003; 41: 582-592Crossref PubMed Scopus (2772) Google Scholar reviewed a large number of studies and concluded that the minimum discernable difference that patients can detect is quite reliable across populations and is approximately equal to one half of a standard deviation of a given HRQOL instrument.Table 1Minimal clinically important difference of various HRQOL scalesInstrumentMCIDReferenceSF-363–5Samsa et al.22.Samsa G. Edelman D. Rothman M.L. et al.Determining clinically important differences in health status measures: a general approach with illustration to the Health Utilities Index Mark II.Pharmacoeconomics. 1999; 15: 141-155Crossref PubMed Scopus (662) Google ScholarSIP3–5Damiano et al.;23.Damiano A.M. Steinberg E.P. Cassard S.D. et al.Comparison of generic versus disease-specific measures of functional impairment in patients with cataract.Med Care. 1995; 33: AS120-AS130PubMed Google Scholar Deyo and Centor24.Deyo R.A. Centor R.M. Assessing the responsiveness of functional scales to clinical change: an analogy to diagnostic test performance.J Chronic Dis. 1986; 39: 897-906Abstract Full Text PDF PubMed Scopus (623) Google ScholarLASA10–20Todd and Funk;25.Todd K.H. Funk J.P. The minimum clinically important difference in physician-assigned visual analog pain scores.Acad Emerg Med. 1996; 3: 142-146Crossref PubMed Scopus (215) Google Scholar Ander et al.;26.Ander D.S. Aisiku I.P. Ratcliff J.J. et al.Measuring the dyspnea of decompensated heart failure with a visual analog scale: how much improvement is meaningful?.Congest Heart Fail. 2004; 10: 188-191Crossref PubMed Scopus (53) Google Scholar Patrick et al.27.Patrick D.L. Gagnon D.D. Zagari M.J. et al.Assessing the clinical significance of health-related quality of life (HrQOL) improvements in anaemic cancer patients receiving epoetin alfa.Eur J Cancer. 2003; 39: 335-345Abstract Full Text Full Text PDF PubMed Scopus (82) Google ScholarKDQ0.5Jaeschke et al.21.Jaeschke R. Singer J. Guyatt G.H. Measurement of health status. Ascertaining the minimal clinically important difference.Control Clin Trials. 1989; 10: 407-415Abstract Full Text PDF PubMed Scopus (3069) Google ScholarHRQOL, health related quality of life; MCID, minimal clinically important difference; SF-36, Short Form-36; SIP, Sickness Impact Profile; LASA, Linear Analog Self-Assessment; KDQ, Kidney Disease Questionnaire. Open table in a new tab HRQOL, health related quality of life; MCID, minimal clinically important difference; SF-36, Short Form-36; SIP, Sickness Impact Profile; LASA, Linear Analog Self-Assessment; KDQ, Kidney Disease Questionnaire. MCIDs are usually established by relying on patients' global ratings of change in their own health. By this approach, subjects are asked to retrospectively judge whether a particular aspect of their health has improved, stayed the same, or worsened, using a single item with several response options. The degree of change on this single global rating scale is then related back to the magnitude of change of an HRQOL instrument to obtain a numerical value denoting the MCID.28.Osoba D. King M. Interpreting QOL in individuals and groups: meaningful differences.in: Fayers P.H.R. Assessing Quality of Life in Clinical Trials: Methods and Practice. 2nd edn,. Oxford University Press, 2005: 243-257Google Scholar Norman et al.33.Norman G.R. Stratford P. Regehr G. Methodological problems in the retrospective computation of responsiveness to change: the lesson of Cronbach.J Clin Epidemiol. 1997; 50: 869-879Abstract Full Text PDF PubMed Scopus (404) Google Scholar describe multiple problems with this approach. The reliability (internal consistency) of any scale is directly related to the number of items on the scale. Therefore, single global ratings will often have poor reliability and validity when compared with multi-item HRQOL scales (although direct evidence for the former is not possible as internal consistency cannot be computed for single item scales). If this were not the case, then the shorter single global rating could simply be substituted for the more complex HRQOL scale. Another drawback of the above approach is that retrospective computations of global health scores depend on the ability of patients to quantify both their present state and their initial state. They then must perform a mental subtraction, and yet there is evidence that this complex judgment of change is psychologically difficult and imprecise.34.Ross M. Relation of implicit theories to the construction of personal histories.Psychol Rev. 1989; 96: 341-357Crossref Scopus (1033) Google Scholar, 35.Schwartz N. Sudman S. Autobiographical Memory and the Validity of Retrospective Reports. Springer-Verlag, New York1994Crossref Google Scholar An alternative to the MCID approach is the distribution-based approach, which relates differences in treatment groups to some measure of variability. The most commonly used distribution-based approach involves calculating the Cohen's standardized effect size, which is simply the mean change divided by the standard deviation.36.Cohen J. Statistical Power Analysis for the Behavioural Sciences. Lawrence Earlbaum, New Jersey1988Google Scholar By this method, effect sizes of 0.2–0.5 are regarded as 'small', 0.5–0.8 as 'moderate', and those above 0.8 are considered 'large'. Effect sizes are influenced by both the magnitude of effect and by variability within the sample. Some investigators have suggested that effect sizes may underestimate clinically important differences.37.Lydick E. Epstein R.S. Interpretation of quality of life changes.Qual Life Res. 1993; 2: 221-226Crossref PubMed Scopus (396) Google Scholar In addition, effect sizes, unlike MCIDs, cannot be used to interpret individual-based differences.28.Osoba D. King M. Interpreting QOL in individuals and groups: meaningful differences.in: Fayers P.H.R. Assessing Quality of Life in Clinical Trials: Methods and Practice. 2nd edn,. Oxford University Press, 2005: 243-257Google Scholar Nonetheless, distribution-based approaches and effect sizes are often useful in meta-analyses, in which the findings from multiple different instruments must be evaluated cumulatively.11.Ross S.D. Fahrbach K. Frame D. et al.The effect of anemia treatment on selected health-related quality-of-life domains: a systematic review.Clin Ther. 2003; 25: 1786-1805Abstract Full Text PDF PubMed Scopus (91) Google Scholar Although there is general agreement that correction of anemia improves HRQOL, the specific domains that are improved and the magnitude of such improvements are less well defined. Tables 2a, 2b, 2c and 2d show the results of representative studies reporting ESA-associated improvements in HRQOL as measured by the SF-36, SIP, LASA, and KDQ, respectively. Given the differing methodologies used to assess HRQOL and the different patient population studies, we did not attempt to perform a meta-analysis. Instead we sought to review high-quality studies selected by preestablished criteria. Studies were selected by searching Medline using the following keywords: (1) quality of life; functional health; (2) chronic kidney disease; chronic renal disease; end-stage renal failure; end-stage renal disease; CKD; hemodialysis; dialysis; predialysis; (3) erythropoietin; epoetin; hemoglobin correction; (4) anemia; hemoglobin; haemoglobin; hematocrit. Using the above keywords and searching for articles written in English and published between 1990 and 2007 resulted in 253 articles. Additional criteria (Figure 2) used to select articles included the following: (1) articles must have been randomized controlled trials (RCTs) or longitudinal clinical trials (LCTs) evaluating the effect of ESAs on HRQOL in adult CKD patients; in the latter type of trial, subjects were used as their own controls; (2) sample size must have been greater than 30 subjects completing the study; (3) subjects must have achieved a minimum increase in Hb of 1.5 g/100 ml or a minimum increase in hematocrit of 4.5%; (4) investigators must have used a validated HRQOL instrument and must have reported the actual data (not simply whether the results were statistically significant or not). With these additional criteria, 11 studies were selected (Tables 2a, 2b, 2c and 2d).Table 2aRepresentative studies reporting an SF-36 scoreΔSF-36 subscales from baseline to end pointAuthorTrialNaN represents the number of subjects in the ESA-treated group (for RCTs) and the total number of subjects (for LCTs) who completed the study.ΔHb (g/100 ml) or Hct (%)bChange in Hb or Hct from baseline to end of study. For those studies with two target hemoglobin groups, data from the "high" hemoglobin group are shown.General healthMental healthPhysical functionPhysical roleSocial functionVitalityBodily painEmotional roleRitz et al. (ACORD)38.Ritz E. Laville M. Bilous R.W. et al.Target level for hemoglobin correction in patients with diabetes and CKD: primary results of the Anemia Correction in Diabetes (ACORD) Study.Am J Kidney Dis. 2007; 49: 194-207Abstract Full Text Full Text PDF PubMed Scopus (131) Google ScholarRCT8511.9 → 13.5+5.33NRNRNRNRNRNRNRSingh et al. (CHOIR)2.Singh A.K. Szczech L. Tang K.L. et al.Correction of anemia with epoetin alfa in chronic kidney disease.N Engl J Med. 2006; 355: 2085-2098Crossref PubMed Scopus (2129) Google ScholarRCT71510.1 → 12.6+3.0+1.7+3.2+6.4+1.3+10.0+0.4+0.8Drueke et al. (CREATE)1.Drueke T.B. Locatelli F. Clyne N. et al.Normalization of hemoglobin level in patients with chronic kidney disease and anemia.N Engl J Med. 2006; 355: 2071-2084Crossref PubMed Scopus (1674) Google ScholarcSF-36 scores were estimated from the published figure.RCT30111.6 → 13.5+4.1+2.7+3.4+2.6+1.8+3.8NRNRBeusterien et al. (NCRHES)39.Beusterien K.M. Nissenson A.R. Port F.K. et al.The effects of recombinant human erythropoietin on functional health and well-being in chronic dialysis patients.J Am Soc Nephrol. 1996; 7: 763-773PubMed Google ScholarLCT47825.5 → 30.1+1.9+4.1+3.7NR+7.5+9.3+1.9NRCHOIR, Correction of Hemoglobin and Outcomes in Renal Insufficiency; CREATE, Cardiovascular Risk Reduction by Early Anemia Treatment with Epoetin-β; NCRHES, National Cooperative Recombinant Human Erythropoietin Study; ACORD, Anemia Correction in Diabetes Study; CES, Canadian Erythropoietin Study Group; NR, not reported; RCT, randomized controlled trial; LCT, longitudinal controlled trial; Hb, hemoglobin; SF-36, Short Form-36.Scores meeting MCID criteria are in bold.a N represents the number of subjects in the ESA-treated group (for RCTs) and the total number of subjects (for LCTs) who completed the study.b Change in Hb or Hct from baseline to end of study. For those studies with two target hemoglobin groups, data from the "high" hemoglobin group are shown.c SF-36 scores were estimated from the published figure. Open table in a new tab Table 2bRepresentative studies reporting a SIP scoreΔSIP subscales from baseline to end pointcHigher scores on the SIP indicate poorer health. Consequently, negative changes in the subscales indicate improvements in health.AuthorTrialNaN represents the number of subjects in the ESA-treated group (for RCTs) and the total number of subjects (for LCTs) who completed the study.ΔHb (g/100 ml) or Hct (%)bChange in Hb or Hct from baseline to end of study. For those studies with two target hemoglobin groups, data from the "high" hemoglobin group are shown.Home managementAlertness behaviorSocial interactionPhysical dimensionPsychosocial dimensionTotal (global) scoreMoreno et al. (SCRQOL)40.Moreno F. Sanz-Guajardo D. Lopez-Gomez J.M. et al.Increasing the hematocrit has a beneficial effect on quality of life and is safe in selected hemodialysis patients. Spanish Cooperative Renal Patients Quality of Life Study Group of the Spanish Society of Nephrology.J Am Soc Nephrol. 2000; 11: 335-342PubMed Google ScholarLCT11510.2 → 12.5NRNRNR-1.3-2.2-1.65Moreno et al.41.Moreno F. Aracil F. Perez R. et al.Controlled study on the improvement of quality of life in elderly hemodialysis patients after correcting end-stage renal disease-related anemia with erythropoietin.Am J Kidney Dis. 1996; 27: 548-556Abstract Full Text PDF PubMed Scopus (112) Google ScholarLCT5721 → 29NRNRNR-5.8-8.2-6.3Deniston et al.42.Deniston O.L. Luscombe F.A. Buesching D.P. et al.Effect of long-term epoetin beta therapy on the quality of life of hemodialysis patients.ASAIO Trans. 1990; 36: M157-M160PubMed Google ScholardBaseline SIP scores were not reported. Therefore, scores represent differences between the ESA-treated versus nontreated groups (mean Hb of nontreated group was 8.3 g/100 ml).LCT175<8.5 → 10.6-9.0-5.0-6.0-2.0-6.0-5.0CES43.Association between recombinant human erythropoietin and quality of life and exercise capacity of patients receiving haemodialysis. Canadian Erythropoietin Study Group.BMJ. 1990; 300: 573-578Crossref PubMed Google ScholarRCT337.1 → 11.7NRNRNR-3.9-8.8-7.8SCRQOL, Spanish Cooperative Renal Patients Quality of Life Study Group; CES, Canadian Erythropoietin Study Group; NR, not reported; RCT, randomized controlled trial; LCT, longitudinal controlled trial; Hb, hemoglobin; SIP, Sickness Impact Profile.Scores meeting MCID criteria are in bold.a N represents the number of subjects in the ESA-treated group (for RCTs) and the total number of subjects (for LCTs) who completed the study.b Change in Hb or Hct from baseline to end of study. For those studies with two target hemoglobin groups, data from the "high" hemoglobin group are shown.c Higher scores on the SIP indicate poorer health. Consequently, negative changes in the subscales indicate improvements in health.d Baseline SIP scores were not reported. Therefore, scores represent differences between the ESA-treated versus nontreated groups (mean Hb of nontreated group was 8.3 g/100 ml). Open table in a new tab Table 2cRepresentative studies reporting a LASA scoreΔLASA subscales from baseline to end pointAuthorTrialNaN represents the number of subjects in the ESA-treated group (for RCTs) and the total number of subjects (for LCTs) who completed the study.ΔHb (g/100 ml)bChange in Hb from baseline to end of study. For those studies with two target hemoglobin groups, data from the "high" hemoglobin group are shown.EnergyActivityOverall quality of lifeSingh et al. (CHOIR)2.Singh A.K. Szczech L. Tang K.L. et al.Correction of anemia with epoetin alfa in chronic kidney disease.N Engl J Med. 2006; 355: 2085-2098Crossref PubMed Scopus (2129) Google ScholarRCT71510.1 → 12.6+16.6+15.