Using the Short Form 6D, as an Overall Measureof Health, to Predict Damage Accrual andMortality in Patients With Systemic LupusErythematosus: XLVII, Results From a MultiethnicUS CohortMONICA FERNANDEZ,1 GRACIELA S. ALARCON,1 GERALD MCGWIN, JR.,1 MARTHA L. SANCHEZ,1

MANDAR APTE,1 LUIS M. VILA,2 AND JOHN D. REVEILLE,3 FOR THE LUMINA STUDY GROUP

Objective. To determine if overall health status as assessed by the Short Form 6D (SF-6D) index, a preference-basedgeneric measure of health, is associated with the occurrence of damage accrual and mortality in patients with systemiclupus erythematosus (SLE).Methods. We studied SLE patients (American College of Rheumatology criteria) from the LUpus in MInorities, NAtureversus nurture cohort (LUMINA), a longitudinal multiethnic cohort. The contribution of the SF-6D as assessed atenrollment to damage accrual at the last visit and mortality was examined. All variables previously shown to bedeterminants of damage accrual and mortality and corroborated by univariable analyses were adjusted for in multiva-riable models (Poisson and Cox proportional hazards regressions, respectively). Damage accrual and mortality were thedependent variables. Similar analyses were performed examining the associations of the Short Form 36 summarymeasures (physical component summary [PCS], mental component summary [MCS]) with these outcomes.Results. In 552 patients, the SF-6D was negatively associated with damage accrual and mortality in the univariableanalyses; the association with damage was confirmed in the multivariable analyses (�2 � 9.020, P � 0.002) but theassociation with mortality was not confirmed (hazard ratio 0.495, 95% confidence interval 0.041–6.038). When the PCSand MCS were evaluated, the PCS, but not the MCS, was found to be associated with damage but not with mortality.Conclusion. The SF-6D (and the PCS) as measured early in the disease course were found to independently predictdamage accrual at the last visit, but not mortality. Although the SF-6D was originally conceived as a utility measure, itmay be used to accurately assess overall health status in patients with SLE.

KEY WORDS. SF-6D; Health-related quality of life; Short Form 36; Damage; Mortality; Systemic lupus erythematosus.

INTRODUCTION

Preference-based generic measures of health are increas-ingly being used to measure quality of life, although they

were originally developed for economic evaluations asutility measures (1,2). The Short Form 6D (SF-6D) (3,4) isa 6-dimensional preference-based scoring system derivedfrom the Short Form 36 (SF-36); the 6 dimensions are

Supported by the National Institute of Arthritis and Mus-culoskeletal and Skin Diseases (grant R01-AR-42503 to theUniversity of Texas Health Science Center [UTHSC] at Hous-ton, the University of Alabama at Birmingham [UAB], andthe University of Puerto Rico Medical Sciences Campus[UPR MSC]), the NIH General Clinical Research Centersprogram (grant M01-RR-02558 to UTHSC at Houston andgrant M01-RR-00032 to UAB), the National Center for Re-search Resources RCMI Clinical Research InfrastructureInitiative award (award 1P20-RR-11126 to UPR MSC) fromthe National Center for Research Resources, and Rheumi-nations, Inc. (grants to support fellowships at UAB).

1Monica Fernandez, MD, Graciela S. Alarcon, MD, MPH,

Gerald McGwin, Jr., PhD, Martha L. Sanchez, MD, MPH,Mandar Apte, MD: University of Alabama at Birmingham;2Luis M. Vila, MD: University of Puerto Rico, San Juan,Puerto Rico; 3John D. Reveille, MD: University of TexasHealth Science Center at Houston.

Drs. Fernandez and Alarcon contributed equally to thiswork.

Address correspondence to Graciela S. Alarcon, MD,MPH, 830 Faculty Office Tower, 510 20th Street South, Bir-mingham, Alabama 35294-3408. E-mail: graciela.alarcon@ccc.uab.edu.

Submitted for publication September 13, 2006; acceptedin revised form February 5, 2007.

Arthritis & Rheumatism (Arthritis Care & Research)Vol. 57, No. 6, August 15, 2007, pp 986–992DOI 10.1002/art.22908© 2007, American College of Rheumatology

ORIGINAL ARTICLE

986

physical functioning, role limitations, social functioning,pain, mental health, and vitality. The SF-6D algorithmgenerates health state values ranging from 1.0 (no difficul-ties with any of the 6 dimensions or perfect health) to0.296 (most impaired level on all 6 dimensions, or worsethan being dead) (5–7).

Although in the majority of studies the SF-6D has beenused for its originally intended purpose, which is as autility measure, it is now also being used to assess overallself-reported health status (or health-related quality of life[HRQOL]). Diseases or clinical situations in which theSF-6D has been used for this purpose include obesity,diabetes, chronic liver disease, coronary heart disease, hu-man immunodeficiency virus, asthma, rheumatoid arthri-tis, total hip arthroplasties, and hip fractures (4,8–15);until now, however, the SF-6D has not been used as autility measure or as a measure of overall health status inpatients with systemic lupus erythematosus (SLE). In con-trast, the SF-36 has been extensively used in SLE (16–21);however, we thought it would be advantageous to obtain asingle numeric value (the SF-6D index) that could be reli-ably used to predict subsequent health outcomes in thesepatients.

We have previously found that patients with SLE par-ticipating in a longitudinal study of outcome function atlower levels than individuals from the general population(22). However, at the time those analyses were conducted,the SF-36 had not been found to be a predictor of eitherdamage accrual or mortality, 2 well-defined outcomes inpatients with SLE. For the present study, we exploredwhether the SF-6D could be a predictor of either outcomeand hypothesized that the worse the overall health statusearly in the course of the disease, the more likely thatdamage accrual and mortality would occur subsequently.Given that LUMINA (LUpus in MInorities, NAture versusnurture) has accrued a large number of patients and yearsof observation since the cohort was first established, wealso reexamined the physical and mental summary mea-sures (physical component summary [PCS] and mentalcomponent summary [MCS]) of the SF-36 as possible pre-dictors of these 2 outcomes.

PATIENTS AND METHODS

As previously described (23), LUMINA is a longitudinalstudy of outcome in patients with SLE. All LUMINA pa-tients met the American College of Rheumatology (ACR)criteria for the classification of SLE (24), had disease du-ration �5 years, were �16 years of age, were of definedethnicity (Hispanic [Mexican or Puerto Rican ancestry],African American, and Caucasian), and lived in the geo-graphic recruitment area of the participating centers (Uni-versity of Alabama at Birmingham, The University of Tex-as-Houston Health Science Center, and The University ofPuerto Rico Medical Sciences Campus). These patientswere, for the most part, referred for medical care andenrolled into LUMINA from either the inpatient or outpa-tient services of these centers and their affiliated practices.Approximately 90% of all patients referred for possibleenrollment into LUMINA agreed to participate and were

enrolled; patients who refused to participate were, in gen-eral, comparable with those recruited into the cohort onsocioeconomic/demographic and clinical features. The in-stitutional review board of each participating center ap-proved the LUMINA study; written informed consent wasobtained from each participating patient according to theDeclaration of Helsinki.

Prior to enrollment, all medical records were reviewedto confirm the patient’s eligibility and to gather socioeco-nomic/demographic and relevant clinical data from thetime of diagnosis to enrollment. Each patient had a base-line visit (T0), and followup visits were conducted every 6months for the first year and yearly thereafter. A LUMINAstudy visit consisted of an interview, a physical examina-tion, and laboratory tests. Data for missed study visits wereobtained, whenever possible, by review of all availablemedical records. The time of diagnosis (TD) was defined asthe time at which patients met 4 ACR criteria for SLE (24).

Variables. As previously reported (25,26), the LUMINAdatabase includes variables from the following domains:socioeconomic/demographic, clinical, immunologic, ge-netic, behavioral, and psychological. These variables weremeasured at T0 and at every subsequent visit. Only thevariables included in these analyses will be described.

Variables from the socioeconomic/demographic domainincluded age, sex, ethnicity, and poverty level (as definedby the US federal government, adjusted for the number ofindividuals in the household) (27). Clinical variables in-cluded total disease duration (the time that elapsed be-tween TD and the last visit [TL]), disease activity, damageaccrual, medications, and mortality.

Disease activity was assessed using the revised SystemicLupus Activity Measure (SLAM-R) (28); the averageSLAM-R score, from T0 to TL, was calculated as a measureof disease activity over time. Damage was measured withthe Systemic Lupus International Collaborating Clinics/ACR Damage Index (29) at T0 and TL. The cumulativeexposure to glucocorticoids (prednisone equivalent) wasalso included and was calculated as the average dose ofprednisone in mg per day.

The SF-6D index was derived from the SF-36 using thealgorithm described by Brazier et al based on standardgamble methodology (30). In short, the original 8 dimen-sions of the SF-36 were reduced to 6 by excluding thegeneral health dimension and combining the physical andmental role limitations dimensions into one. The finalindex includes items from the following dimensions: 3items from physical functioning, 2 from role limitations, 1from social functioning, 2 from pain, 1 from mental health,and 1 from vitality; this index provides a single numericvalue ranging from 0.296 (worst possible health, worsethan being dead) to 1.0 (perfect health).

Statistical analyses. The contributions of the SF-6D andthe 2 measures of the SF-36 (PCS and MCS) as assessed atT0 to damage accrual at TL and to mortality were exam-ined first by univariable analyses. Multivariable modelswith damage accrual and mortality as the dependent vari-ables and all variables significant in the univariable ana-

Overall Measure of Health Using the SF-6D 987

lyses as independent variables were examined next. Giventhe distribution of the damage scores, damage accrual atTL was examined by Poisson regressions. For the mortalityanalyses, Cox proportional hazards regression modelswere examined. Two sets of models were examined foreach of these outcomes, one in which the SF-6D wasincluded as an independent variable and the other inwhich the PCS and MCS were included instead. Becausethe SF-6D index is a mathematical derivation of the SF-36,the PCS and MCS and the SF-6D index were not includedin the same model. However, given the interaction be-tween these constructs and poverty, and given that povertyis a predictor of both damage and mortality, additionalanalyses were conducted using these interaction terms.Statistical significance was defined as a P value �0.05. Allstatistical analyses were performed using SAS software,version 9.1 (SAS Institute, Cary, NC).

RESULTS

A total of 552 patients were studied. Of the 552 patients,491 (89%) were women. There were 105 (19%) TexanHispanics, 100 (18%) Puerto Rican Hispanics, 183 (33%)African Americans, and 164 (30%) Caucasians. Theirmean � SD age and total disease duration in years were36.8 � 12.6 and 5.4 � 3.5, respectively.

Damage. Univariable analyses. First, the mean and me-dian damage scores for the different variables were exam-ined; continuous variables were divided into categoriesusing either biologically plausible cutoff values (age, dis-ease duration) or the median value for the variable beingexamined (SLAM-R score, glucocorticoid dose, and SF-6Dand SF-36 PCS and MCS scores). Overall, higher damagescores were found in patients who were older, male, Afri-can American, and Texan-Hispanic, living below the pov-erty line, those who had longer disease duration, higherSLAM-R scores, and lower SF-36 PCS and MCS scores andSF-6D scores. These data are shown in Table 1. Both the T0SF-6D and the SF-36 summary measures were found to benegatively associated with the later occurrence of damage.In addition, variables previously shown to be associatedwith damage accrual (31) were also found to be significantin these analyses (32). These data are depicted in Table 2.

Multivariable analyses: SF-6D. Of the 552 patients, only501 could be included in the multivariable analyses ofdamage due to missing values for either the dependent orthe independent variables. The SF-6D was negatively as-sociated with the occurrence of damage at TL after adjust-ing for age, ethnicity, sex, poverty, glucocorticoid use,disease duration, disease activity at TD, and damage ac-crual at T0 (or first recorded; �2 � 9.020, P � 0.0027).These data are shown in Table 3.

Multivariable analyses: SF-36. When the PCS and MCSmeasures of the SF-36 were entered into the Poisson re-gression, the variables retained were the same as in theprevious model. The PCS was also found to be negativelyassociated with damage in this model (�2 � 5.60, P �0.0179) but the MCS was not (data not shown).

Alternative models: interaction terms. When the inter-action term between poverty and the SF-6D index was

added to the model, neither poverty nor the interactionterm was a significant predictor of damage accrual but theSF-6D was of borderline significance (P � 0.066). In con-trast, when similar analyses were performed including theinteraction term between poverty and the PCS, neither thePCS nor poverty remained significant but the interactionterm was of borderline significance (P � 0.057).

Mortality. Univariable analyses. Variables associatedwith mortality by Cox proportional hazards regression uni-variable analyses were entirely consistent with previouslyreported analyses of mortality conducted in our cohort(33). The SF-6D and the PCS measure of the SF-36 (but notthe MCS) were negatively associated with mortality inthese analyses. These data are depicted in Table 4.

Table 1. Mean and median Systemic LupusInternational Collaborating Clinics/American College of

Rheumatology Damage Index scores at last visit inLUMINA (LUpus in MInorities: NAture versus nurture)

patients as per categories of the differentvariables examined*

Variable Means Medians

Age, years�50 1.63 1�50 2.38 2

SexFemale 1.71 1Male 1.98 1

EthnicityHispanic Texan 2.22 1Hispanic Puerto Rican 0.56 0African American 2.31 2Caucasian 1.40 1

Poverty level†No 1.45 1Yes 2.23 1.5

Disease duration, years‡�5 1.35 1�5 2.20 1.5

Average SLAM-R score�10 1.13 1�10 2.46 2

Average GC dose,prednisone mg/day

�5 1.45 1�5 2.01 1

SF-6D score at T0�0.6 1.44 1�0.6 1.96 1

SF-36 PCS score at T0�35 1.37 1�35 1.98 1

SF-36 MCS score at T0�40 1.62 1�40 1.83 1

* SLAM-R � revised Systemic Lupus Activity Measure; GC � glu-cocorticoid; SF-6D � Short Form 6D; SF-36 � Short Form 36; PCS �physical component summary; MCS � mental component sum-mary.† As per the US federal government guidelines (27).‡ From diagnosis to last visit.

988 Fernandez et al

Multivariable analyses: SF-6D. At the time this studywas performed, 64 deaths had been reported. The analysesincluded 52 of these 64 deaths; the others could not beincluded because of missing values for some of the inde-pendent variables included in the model. By Cox multiva-riable proportional hazards regression analyses, and afteradjusting for age, ethnicity, sex, poverty, disease activity atT0, and damage accrual at T0 (or first recorded), the SF-6Dwas not associated with the occurrence of mortality (haz-ard ratio [HR] 0.495, 95% confidence interval [95% CI]0.041–6.038). These data are depicted in Table 5.

Multivariable analyses: SF-36. When the PCS measureof the SF-36 was included instead of the SF-6D, the result-ing model was consistent with the SF-6D model; the PCSwas not retained in the model (HR 1.014, 95% CI 0.959–1.073).

Alternative models. When poverty was excluded fromthe Cox regressions, the PCS and the SF-6D became strongpredictors of mortality. If poverty, the SF-6D (or the PCS),and the corresponding interaction terms were included,the interaction term was significant in the case of theSF-6D (and the SF-6D and poverty were of borderlinesignificance); this was not the case for the PCS regressionin which neither the PCS nor the interaction term re-mained significant (data not shown).

Table 2. Variables associated with damage accrual atlast visit by Poisson univariable regression analyses*

Feature Chi-square P

Age, years 12.39 � 0.001Male sex 2.25 0.133Ethnicity†

Hispanic Texan 87.53 � 0.001African American 101.26 � 0.001Caucasian 38.22 � 0.001

Poverty level‡ 44.47 � 0.001Total disease duration, years§ 109.14 � 0.001Average SLAM-R score 180.32 � 0.001SDI score¶ 437.90 � 0.001Average GC dose in mg 16.40 � 0.001SF-6D score at T0 53.63 � 0.001SF-36 PCS score at T0 63.33 � 0.001SF-36 MCS score at T0 28.59 � 0.001

* All associations are positive except for the SF-6D and the PCS andMCS measures of the SF-36. SDI � Systemic Lupus InternationalCollaborating Clinics/American College of Rheumatology DamageIndex; see Table 1 for additional definitions.† Hispanic Puerto Rican is the reference group.‡ As per US federal government guidelines (27).§ From diagnosis to last visit.¶ At T0 or first recorded.

Table 3. Variables independently associated withdamage accrual at last visit by Poisson

regression analyses*

Feature Chi-square P

Age, years 14.99 � 0.0001Male sex 1.51 0.2196Ethnicity†

Hispanic Texan 36.04 � 0.0001African American 25.33 � 0.0001Caucasian 12.16 0.0005

Poverty level‡ 19.74 � 0.0001Total disease duration, years§ 103.76 � 0.0001SLAM-R score at diagnosis 16.31 � 0.0001SDI score¶ 171.79 � 0.0001Average GC dose, mg

prednisone/day3.99 0.0459

SF-6D score at T0 9.02 0.0027

* All associations are positive except for the SF-6D. SDI � SystemicLupus International Collaborating Clinics/American College ofRheumatology Damage Index; see Table 1 for additional definitions.† Hispanic Puerto Rican is the reference group.‡ As per US federal government guidelines (27).§ From diagnosis to last visit.¶ At T0 or first recorded.

Table 4. Variables associated with mortality at 10 yearsby univariable Cox proportional hazard regression

analyses*

FeatureHazard

ratio 95% CI P

Age, years 1.009 0.990–1.028 0.356Male sex 1.126 0.512–2.474 0.768Ethnicity†

Hispanic Texan 1.836 0.891–3.785 0.099Hispanic Puerto Rican 0.213 0.028–1.639 0.137African American 2.029 1.065–3.866 0.031

Poverty level‡ 2.304 1.404–3.779 0.001SLAM-R score 1.145 1.111–1.180 � 0.001SDI score§ 1.482 1.277–1.719 � 0.001SF-6D score at T0 0.030 0.003–0.272 0.001SF-36 MCS score at T0 0.983 0.954–1.012 0.247SF-36 PCS score at T0 0.944 0.913–0.975 � 0.001

* 95% CI � 95% confidence interval; SDI � Systemic Lupus Inter-national Collaborating Clinics/American College of RheumatologyDamage Index; see Table 1 for additional definitions.† Caucasian is the reference group.‡ As per US federal government guidelines (27).§ At T0 or first recorded.

Table 5. Multivariable Cox proportional hazardregression analysis of mortality at 10 years*

FeatureHazard

ratio 95% CI P

Age, years 1.031 1.008–1.053 0.0068Male sex 1.337 0.558–3.202 0.5147Ethnicity†

Hispanic Texan 1.292 0.548–3.047 0.5584Hispanic Puerto Rican 0.331 0.042–2.616 0.2945African American 0.926 0.407–2.108 0.8550

Poverty level‡ 2.466 1.328–4.578 0.0043SLAM-R score at T0 1.113 1.064–1.164 � 0.0001SDI score§ 1.202 1.001–1.442 0.0483SF-6D score at T0 0.495 0.041–6.038 0.5818

* 95% CI � 95% confidence interval; SDI � Systemic Lupus Inter-national Collaborating Clinics/American College of RheumatologyDamage Index; see Table 1 for additional definitions.† Caucasian is the reference group.‡ As per US federal government guidelines (27).§ At T0 or first recorded.

Overall Measure of Health Using the SF-6D 989

DISCUSSION

Self-perceived HRQOL has become increasingly importantin biomedical clinical research. In the LUMINA cohort, alongitudinal study of outcomes, we have previously ex-plored intermediate and long-term outcomes includingdisease activity, damage accrual, self-reported HRQOL,and mortality (16,22,32,34–36).

Although the SF-6D was originally designed for eco-nomic evaluations as a utility measure, it has been shownto be a reliable instrument to assess HRQOL (37,38). Wehave now taken advantage of having the data necessary toderive the SF-6D (since the SF-36 had been administeredto our patients) to assess its impact, when measured earlyin the disease course, on both damage accrual and mortal-ity. We perceive the SF-6D to be a multidimensional mea-sure of HRQOL represented by a single numeric valuespanning the range of health status. This single value maybe easier to grasp for clinicians and researchers alike thanthe different scales and summary measures of the SF-36;after all, perceived health, whether affected primarily inits mental or physical domains, is but one construct. Wefound that lower SF-6D values early in the disease courseindependently predict damage accrual at TL; this was notthe case for mortality because the SF-6D was not retainedin the model.

In parallel to examining the SF-6D index, we also reex-amined the impact of the SF-36 summary measures (PCSand MCS) on both damage and mortality, given that notonly has the LUMINA cohort accrued more years of obser-vation, but also more patients now constitute this cohort.In previous analyses, significant and negative correlationsbetween damage accrual at TL and the PCS and MCSmeasures of the SF-36 were found by univariable analyses;however, these variables were not retained in the multiva-riable analyses (32). In the present study, we found thatboth summary measures of the SF-36 were negatively as-sociated with damage accrual at TL by univariable analy-ses; in the multivariable analyses, however, the PCS, butnot the MCS, remained negatively associated with damageaccrual, albeit the relationship was of lesser magnitudethan for the SF-6D index. Although the SF-6D is a mathe-matical derivation of the SF-36, the manner in which it isderived and the items and dimensions included may betterrepresent overall self-reported HRQOL and thus influencea patient’s subsequent outcomes in a more decisive man-ner than the summary measures of the SF-36. In short, theSF-6D may be somewhat more sensitive than the SF-36 todetect those changes in HRQOL and more likely to detectsubsequent impact on damage, particularly consideringthat the lower levels of the SF-6D index are much moresensitive than the upper levels (3). This of course will needto be corroborated in other patient populations before it isfully accepted. Conversely, damage accrual occurringearly in the course of the disease has been found to be anindependent predictor of overall physical function, butnot mental function (19,22). Other authors have not founda relationship between HRQOL and damage accrual ineither direction (20,39). It also should be noted that acertain degree of interaction between poverty and thesemeasures of HRQOL was found. When interaction terms

were added to the damage models, the SF-6D remained ofborderline significance whereas the PCS lost its signifi-cance altogether.

Patients with SLE are now expected to live years, if notdecades, after their diagnosis, although their life expect-ancy is still below that of the general population (40,41);identifying the factors affecting this terminal outcome ofthe disease is therefore quite relevant. Mortality in lupushas been associated with socioeconomic factors such asage, ethnicity, and poverty, as well as with clinical factorsincluding disease activity and damage accrual (33,42–44),but the role of self-perceived HRQOL as a predictor ofmortality in patients with lupus has not been supported byus or other researchers. Using either the SF-6D or thesummary measures of the SF-36 as self-reported measuresof HRQOL, we have not been able to demonstrate their roleas predictive factors of mortality; however, it is entirelypossible that their effect is not direct but rather is mediatedby their effect on damage, which is known to affect sur-vival (33). To this end, it is important to point out thatpatients with lupus may be experiencing a longer survivalthan in years past, yet their self-perceived HRQOL is lessthan optimal, in part because of the damage being accrued.

The alternative explanation, of course, is that poverty issuch a strong predictor of mortality and that the effect ofHRQOL ascertained either by the summary measures ofthe SF-36 or by the SF-6D cannot be fully appreciatedunless poverty is removed from the models. In fact, ouralternative models support this assertion. These data,taken together with the damage data discussed above, un-derscore the importance of poverty in the intermediate andlong-term outcomes of a disease like lupus; we have rec-ognized this fact from the very first analyses of mortalityconducted in our cohort (33) and in recent analyses ofdamage (31).

The need to measure HRQOL in the assessment of pa-tients with SLE enrolled in either randomized clinicaltrials or in longitudinal observational studies has beenrecognized by the Outcome Measures in RheumatologyClinical Trials (OMERACT) group and by regulatory agen-cies (45,46). In fact, functional assessment is now an inte-gral part of ongoing clinical trials aimed at the study ofnew pharmacologic and biologic compounds (47,48) forthe treatment of patients with lupus. Whether we willcontinue to use the SF-36 or instead turn to the SF-6D toascertain this construct cannot be determined from ourwork alone and the published literature to date. Our studydemonstrates that low levels of self-perceived overallhealth early in the course of the disease may be premoni-tory of poor later outcomes and that physicians caring forthese patients should be alert to this fact. Identifying andtreating these patients appropriately and promptly is nec-essary if the long-term deleterious outcomes of the diseaseare to be prevented.

AUTHOR CONTRIBUTIONS

Dr. Alarcon had full access to all of the data in the study andtakes responsibility for the integrity of the data and the accuracyof the data analysis.Study design. Fernandez, Alarcon, McGwin, Sanchez.

990 Fernandez et al

Acquisition of data. Fernandez, Vila, Reveille.Analysis and interpretation of data. Fernandez, Alarcon, Mc-Gwin, Apte, Vila.Manuscript preparation. Fernandez, Alarcon, McGwin, Sanchez,Reveille.Statistical analysis. McGwin, Apte.

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