Objective: To evaluate excess mortality across calendar time comparing HIV-infected patients receiving combination antiretroviral therapy (cART) with the general Chinese population.
Methods: Patients receiving free cART through the National Free Antiretroviral Therapy Program (NFATP) between January 1, 2003, and December 31, 2009, were included. Observed mortality rates, excess mortality rates, and standardized mortality ratios were calculated by calendar periods. Factors associated with excess mortality across calendar time were evaluated in multivariable Poisson regression models.
Results: Among 64,836 HIV-infected patients, the observed and excess mortality rates in 2003–2004 were 9.5 deaths per 100 person-years [95% confidence interval (CI): 8.8 to 10.2] and 9.1 (95% CI: 8.5 to 9.8); in 2008–2009, these decreased to 5.6 (95% CI: 5.4 to 5.8) and 5.2 (95% CI: 5.0 to 5.4), respectively. The adjusted excess hazard ratio (eHR) for 2003–2004 in comparison to 2008–2009 was 1.27 (95% CI: 1.11 to 1.45). Patients initiating cART at CD4 cell counts <50 cells per microliter in comparison with ≥350 cells per microliter had an adjusted eHR of 9.92 (95% CI: 8.59 to 11.44). Patients starting cART at older ages also had greater excess mortality with an eHR of 1.63 (95% CI: 1.47 to 1.82) comparing ages ≥45 to 18–29 years. Standardized mortality ratio results were consistent with those for excess mortality.
Conclusions: Substantial decreases in excess mortality were observed from 2003 to 2009 in China among HIV-infected patients receiving free cART. However, mortality among HIV-infected patients remained higher than the general Chinese population. As more efficacious first- and second-line cART regimens become increasingly available to Chinese HIV-infected patients, further reductions in overall and excess mortality are likely.
*Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC;
†Division of Treatment and Care, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China;
‡Division of Infectious Diseases, School of Medicine, University of North Carolina, Chapel Hill, NC; and
§Division of Infectious Diseases, Beijing Ditan Hospital Capital Medical University, Beijing, China.
Correspondence to: Fujie Zhang, MD, PhD, Division of Treatment and Care, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing, China 100027 (e-mail: email@example.com).
Supported by grants from National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention; Grants P30-AI50410 from the National Institutes of Health; UNC AIDS International Training and Research Programs grant (5 D43 TW001039-13) from the John E. Fogarty International Center, National Institutes of Health. The funding sources did not participate in the study design, collection, analysis and interpretation of data; in the writing of the manuscript; or in the decision to submit the article for publication.
J.J.E. has received consulting fees from Tibotec/Janssen, Bristol-Myers Squibb, GlaxoSmithKline, ViiV and Gilead, and Merck, and grant support from GlaxoSmithKline, ViiV, Merck, and Bristol-Myers Squibb. The other authors have no conflicts of interest to disclose.
M.S.C. and F.Z. contributed equally to this work.
Received November 21, 2012
Accepted March 25, 2013
Combination antiretroviral therapy (cART) provision enables HIV-infected patients to suppress HIV replication,1–3 leading to substantially lower morbidity and mortality in both resource-rich and resource-poor areas of the world.4,5 A number of previous studies have observed notable reductions in mortality across calendar time with increasing uptake of more efficacious cART.6–8 However, mortality among HIV-infected patients remains higher in resource poor areas even where cART is available.9
Reductions in mortality from HIV infection have also been narrowing the gap in life expectancy comparing HIV-infected patients with the general population.10–13 Among some HIV-infected patients, life expectancy may approach that observed in the general population.14,15 For example, among West and South African patients participating in the International Epidemiological Databases to Evaluate AIDS project who initiated cART at higher CD4 counts, life expectancy estimates approach those of HIV-uninfected individuals.16 Mortality and life expectancy contrasts comparing HIV-infected patients receiving cART to the general population assess the effectiveness of provided HIV therapy at a population level. These types of analyses also provide data for policy makers for assessing future needs of HIV-infected patients and in planning allocation of health care and other resources.
The Joint United Nations Programme on HIV/AIDS estimated that as of 2009, 740,000 (range 540,000–1,000,000) adults and children were living with HIV in China.17 Since 2002, HIV-infected patients in China have had access to free cART through the National Free Antiretroviral Treatment Program (NFATP),18 and as of 2009, over 80,000 patients received cART through this program.19 As elsewhere around the world, HIV-infected patients receiving cART experience notable reductions in morbidity and mortality in China.19–21 Although NFATP only launched the national free cART program in the last decade, notable decreases in mortality across calendar time have already been reported.22 However, previous work on this has concentrated on internal comparisons of mortality among HIV-infected patients overtime, and therefore cannot distinguish mortality time trends among HIV-infected patients from temporal trends in the Chinese population. In the present study, we compare mortality estimates between HIV-infected patients receiving cART through NFATP with the general Chinese population from 2003 to 2009. We estimated both excess mortality and standardized mortality ratios (SMRs) over calendar time and evaluated risk factors for excess mortality.
Patients receiving free cART through NFATP between January 1, 2003, and December 31, 2009, were included.18,23,24 Patients were eligible for cART if they had a CD4 count below 200 cells per microliter (increased to 350 cells per microliter in 2008), a total lymphocyte count <1200 cells per microliter, or a World Health Organization stage III or IV clinical condition.25 Standardized paper-based case report forms were completed by local health workers. Information included demographic data, HIV exposure route, clinical symptoms and signs, cART administered, and laboratory test results. Subsequent follow-up visits occurred at 2, 4, 8, and 12 weeks after cART initiation, and then every 3 months thereafter. We excluded patients who did not have information on area of residence (n = 10,669) and who did not have any follow-up visit information before December 15, 2009 (n = 714). This study was approved by the Institutional Review Board at the University of North Carolina at Chapel Hill and the National Center for AIDS/STD Control and Prevention at China Center for Disease Control and Prevention.
Factors measured at the first visit included age, sex, likely HIV exposure route, initial cART regimen, CD4 cell count, type of health care setting, and area of residence (rural versus urban). Antiretroviral therapy regimens were categorized as neviripine (NVP) with lamivudine (3 TC) and either zidovudine (AZT) or stavudine (D4T), efavirenz (EFV) with 3 TC and either AZT or D4T, NVP and didanosine (DDI) and either AZT or D4T, and all other regimens. HIV exposure route included infection through blood transfusion/former plasma donation, sexual transmission, and injection drug use (IDU). Information on death, including reason and date of death, was available through the NFATP treatment withdrawal forms. These forms were also completed by local health workers and sent to central NFATP offices by DataFax (Clinical DataFax Systems, Hamilton, ON, Canada). Forms were completed on all patients known to have died at the local level through passive surveillance. Mortality data for the general Chinese population was obtained from the China Health Statistic Year Book, 2004–2010.26 These national death statistics are based on a passive surveillance system, that is, the Ministry of Health–vital registration system, to report death cases to a central national repository.27
Person-time was calculated from the date when patients initiated cART to the date of death or date of censoring. Patients were censored either at the date of withdrawal from NFATP or December 31, 2009, whichever occurred first. The reason for withdrawal included loss to follow-up, treatment interruption, or transferring to another health care facility. Loss to follow-up was defined as missing more than 3 visits, and we used the latest date seen in clinic as the date of withdrawal.
Observed mortality rates were calculated as number of deaths divided by person-years at risk and corresponding 95% confidence intervals (95% CIs) were calculated as28:
where R is the observed mortality rate and n is the number of deaths. Expected number of deaths was estimated by applying the probability of death in the general Chinese population to the study population in each calendar year. Patients were matched to the general population on age (by 5-year age group), sex, area of residence (urban versus rural), and calendar year.
Excess mortality rates were calculated as the difference between observed deaths in the study population and that expected based on estimates from the general population. SMRs were calculated as the ratio of the observed number of deaths in the study population to that expected from estimates based on the general population. As measures of precision, we calculated 95% CIs for both excess mortality rates and SMRs.28 Excess mortality rates and SMRs were estimated within strata defined by calendar year interval (2003–2004, 2005–2007, and 2008–2009). This categorization was chosen to minimize heterogeneity within groups, correspond with major therapeutic changes across calendar time, and preserve adequate sample sizes within strata. Further stratification of estimates was done according to patients' age, sex, HIV exposure route, CD4 count at cART initiation, area of residence, type of health care settings, and type of first cART regimen received.
We further evaluated changes in excess mortality across calendar time in multivariable Poisson regression models.29 In this relative survival model, the observed number of deaths in each patient stratum was modeled with a Poisson process, and we used the expected number of deaths in each stratum as an offset. Time was categorized into 1-year increments from cART initiation, assuming a piecewise constant hazard within each year after starting cART. Excess hazard ratios (eHRs) and associated 95% CIs were obtained as the antilog of the coefficient from this relative survival model. We examined changes in relative survival across calendar time adjusting for age, sex, HIV-exposure category, CD4 count, initial cART regimen, type of health care setting, and area of residence. In this case, the interpretation of eHR comparing calendar years is similar to other survival models, such that the index group of patients experience an instantaneous risk of death “eHR” times the risk among patients in the reference group, accounting for expected background mortality and the other patient characteristics included in the model. In all analyses, hypothesis testing was 2-sided and an alpha of 0.05 was used to indicate a statistically significant difference. All analyses were done using SAS (version 9.2; SAS Institute, Cary, NC).
Overall, 64,836 HIV-infected patients with known area of residence initiated cART in the Chinese NFATP between 2003 and 2009 and were included in this analysis. The proportion of patients receiving treatment increased up overtime, and almost half of patients initiated cART during 2008 and 2009 (47%) (Table 1). The median age at cART initiation was 38 years (interquartile range: 33–46), 40% of patients were women, and 70% lived in rural areas. In more recent years, patients appeared younger at cART initiation, were more likely to be men, and more likely to live in urban areas. In 2003 and 2004, 95% of patients were infected through blood transfusion/former plasma donation, and this decreased to 18% by 2008 and 2009.
The median CD4 count at cART initiation decreased across time from 223 cells per microliter in 2003–2004 to 141 cells per microliter in 2008–2009. Although NVP remained the most common anchor agent provided, the use of 3 TC replaced DDI in 2005–2006. Specifically in 2003–2004, patients predominantly received NVP and DDI with either AZT or D4T (89%), and in comparison, in 2008–2009, the most common first cART regimen was NVP and 3 TC with either AZT or D4T (73%).
Patients were followed on average for a median of 1.5 years (interquartile range: 0.5–3.4), contributing a total of 135,509 person-years of follow-up (Table 2). Overall, 13% of patients were known to have died (n = 8577), with an observed mortality rate of 6.3 deaths per 100 person-years (95% CI: 6.2–6.4). The crude observed mortality rate decreased across calendar time from 9.5 to 5.6 deaths per 100 person-years from 2003–2004 to 2008–2009, respectively.
The overall excess mortality rate was 6.0 deaths per 100 person-years (95% CI: 5.9 to 6.1). Excess mortality fell from 9.1 deaths per 100 person-years (95% CI: 8.5 to 9.8) in 2003–2004 to 5.2 deaths per 100 person-years (95% CI: 5.0 to 5.4) in 2008–2009 (Table 2). The reductions in excess mortality rates across calendar time were evident within all strata of patient characteristics, including age, sex, CD4 count at cART initiation, and type of initial cART (Table 3). In unadjusted analyses, excess mortality rates were higher among older patients in each stratum of calendar years, although younger patients in 2003–2004 also had high excess mortality. After adjustment for other patient characteristics, including age, sex, HIV exposure route, CD4 count, number of baseline symptoms, initial cART regimen, area of residence, and health care setting, the adjusted excess mortality rates were higher in older patients across all calendar periods (data not shown here). The most dramatic reductions in unadjusted excess mortality rates across calendar time occurred among patients with low CD4 counts at cART initiation, and comparable results were obtained in all strata of CD4 in the adjusted analyses (data not shown here).
The overall SMR was 20.1 (95% CI: 19.7 to 20.5). The SMR decreased from 30.8 (95% CI: 28.6 to 33.1) to 17.0 (95% CI: 16.5 to 17.6) from 2003–2004 to 2008–2009 (Table 2), respectively. In general, SMR results stratified by patient characteristics were comparable to results observed for excess mortality rates (Table 4). As observed with excess mortality rates, the reduction in SMR across calendar time was most dramatic among patients initiating cART at low CD4 counts. Among patients with CD4 counts below 50 cells per microliter, the SMR declined from 103.6 (95% CI: 86.2 to 124.5) to 32.2 (95% CI: 30.5 to 34.0) from 2003–2004 to 2008–2009, respectively.
The adjusted excess mortality rate decreased from 2003–2004 to 2008–2009, with an eHR of 1.27 (95% CI: 1.11 to 1.45), indicating the risk of death was nearly 30% higher in 2003–2004 than 2007–2008, adjusting for background mortality and other patient characteristics including age, sex, HIV exposure route, area of residence, health care setting, CD4 count, number of baseline symptoms, and initial cART regimen (Table 5). Patients who were older at cART initiation were at a greater risk of dying with an eHR of 1.63 (95% CI: 1.47 to 1.82) comparing patients aged older than 45 years to those aged 18–29 years. Men, patients living in rural areas, and those exposed to HIV through IDU were also at higher risk of death. Patients who received care at larger and centralized medical care facilities seemed to be at lower risk than those who received care at smaller local centers. Excess mortality decreased with increasing CD4 counts at cART initiation, with patients who started cART with CD4 counts less than 50 cells per microliter at almost 10 times the risk of death compared with patients with CD4 counts greater than 350 cells per microliter (eHR = 9.92; 95% CI: 8.59 to 11.44).
In this study, including over 64,000 HIV-infected patients initiating cART in China, we found that both observed and excess mortality rates decreased more than 30% from 2003 to 2009. Mortality ratios standardized to the general Chinese population also decreased by over 30% from 2003 to 2009. The decreases in excess mortality rates and SMRs across calendar time were relatively consistently observed within all patient demographic and clinical characteristics, and after adjusting for a number of factors including age, CD4 count, and cART regimen at therapy initiation, excess mortality decreased by over 20% from 2003–2004 to 2008–2009. These findings are consistent with previous studies that have reported reductions in observed and expected mortality rates and SMRs across calendar time among patients initiating cART in both resource-rich and resource-poor areas of the world.15,16,30–32
The observed mortality rate in this study population (6 deaths per 100 person-years) was higher in comparison to results from resource wealthy areas of the world (1 death per 100 person-years),31 but lower than that observed in sub-Saharan Africa (8 deaths per 100 person-years).16 The overall excess mortality we observed was similar to estimates from sub-Saharan Africa (6 vs 7 deaths per 100 person-years, respectively), as were the SMRs (20 and 19, respectively),16 but higher than reported in Europe and North America (excess mortality rate = 2 deaths per 100 person-years30 and SMR = 331).
Notwithstanding the substantial decreases in mortality rates across calendar time, HIV-infected patients in this study population consistently had greater excess mortality in comparison to the general Chinese population. However, there were notable differences in excess mortality rates among groups of patients defined by demographic and clinical characteristics. Among some groups of patients, mortality was less than 10 times the general population, whereas among other groups, this rose to over 100 times. The greatest differences in mortality were observed within CD4 count and age strata. The lowest excess mortality rates were among patients initiating cART at CD4 counts greater than 350 cells per microliter. This group of patients had less than 10 times the mortality of the general population in all calendar years. In comparison, the highest excess mortality rates were observed among patients initiating cART with CD4 counts less than 50 cells per microliter. This group of patients had over 30 times the mortality of the general population even in the most recent calendar years. In adjusted analyses, patients starting cART with CD4 counts less than 50 cells per microliter had nearly a 10-fold higher excess mortality compared with patients initiating cART at CD4 counts greater than 350 cells per microliter. These findings have been consistently reported from all areas of the world12,16 and underscore recent recommendations that cART be initiated at higher CD4 counts to optimize overall survival33–35 and that additional efforts are needed for earlier HIV diagnosis and treatment initiation among many HIV-infected patients.36
Overall excess mortality rates increased with increasing age. In multivariable analyses, adjusting for CD4 count and other patient characteristics patients at least 45 years of age had over 1.6 times excess mortality in comparison to patients aged 18–29 years. Other independent factors associated with excess mortality in multivariable analyses included being a male, patients infected through IDU in comparison to sexual transmission, patients residing in rural versus urban areas, and patients receiving HIV care at local health care centers in comparison to larger centralized hospital settings. Previous studies have also reported older age, male sex, and IDU as risk factors for excess mortality.9,30,32
It is possible that the HIV-infected patients in this study population were different from the general population in other characteristics that we were not able to account for (ie, age, sex, area of residence, and calendar year).13 In other words, HIV-infected patients in China may be at greater risk of death than the general population for reasons other than HIV, such as a higher prevalence of other comorbidities (eg, hepatitis B or C infection). Death ascertainment relied on reports to HIV care providers, rather than links with centralized death registries; therefore, we may be underestimating the true mortality rates. Mortality rates of the general Chinese population were based on a passive surveillance system, the Ministry of Health–vital registration system, which may not capture all deaths in each province, with some variation by province. We were also unable to account for duration of HIV infection or virological or immunological response to cART due to insufficient data. Observed mortality rates, excess rates, and SMRs would likely be lower among patients with better response to cART.
In summary, among HIV-infected patients receiving cART through the Chinese NFATP, we have observed substantial decreases in excess mortality in comparison to the general Chinese population from 2003 to 2009. Further reductions will likely be achieved because NFATP is able to provide more efficacious first- and second-line cART regimens. Our results indicate that further reductions in mortality will follow if patients are identified earlier after HIV infection and are successfully linked with HIV care.
The authors thank the staff of the local counties' Centers for Disease Control, who spent numerous hours and great effort working with us in obtaining, verifying, and cleaning the data used in this study.
1. May MT, Sterne JA, Costagliola D, et al.. HIV treatment response and prognosis in Europe and North America in the first decade of highly active antiretroviral therapy: a collaborative analysis. Lancet. 2006;368:451–458.
2. Srikantiah P, Ghidinelli M, Bachani D, et al.. Scale-up of national antiretroviral therapy programs: progress and challenges in the Asia Pacific region. AIDS. 2010;24(suppl 3):S62–S71.
3. Keiser O, Anastos K, Schechter M, et al.. Antiretroviral therapy in resource-limited settings 1996 to 2006: patient characteristics, treatment regimens and monitoring in sub-Saharan Africa, Asia and Latin America. Trop Med Int Health. 2008;13:870–879.
4. Cornell M, Grimsrud A, Fairall L, et al.. Temporal changes in programme outcomes among adult patients initiating antiretroviral therapy across South Africa, 2002-2007. AIDS. 2010;24:2263–2270.
5. ART-CC. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008;372:293–299.
6. Ewings FM, Bhaskaran K, McLean K, et al.. Survival following HIV infection of a cohort followed up from seroconversion in the UK. AIDS. 2008;22:89–95.
7. Porter K, Babiker A, Bhaskaran K, et al.. Determinants of survival following HIV-1 seroconversion after the introduction of HAART. Lancet. 2003;362:1267–1274.
8. Etard JF, Ndiaye I, Thierry-Mieg M, et al.. Mortality and causes of death in adults receiving highly active antiretroviral therapy in Senegal: a 7-year cohort study. AIDS. 2006;20:1181–1189.
9. Braitstein P, Brinkhof MW, Dabis F, et al.. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet. 2006;367:817–824.
10. Keiser O, Taffe P, Zwahlen M, et al.. All cause mortality in the Swiss HIV cohort study from 1990 to 2001 in comparison with the Swiss population. AIDS. 2004;18:1835–1843.
11. Lohse N, Hansen AB, Pedersen G, et al.. Survival of persons with and without HIV infection in Denmark, 1995-2005. Ann Intern Med. 2007;146:87–95.
12. Jensen-Fangel S, Pedersen L, Pedersen C, et al.. Low mortality in HIV-infected patients starting highly active antiretroviral therapy: a comparison with the general population. AIDS. 2004;18:89–97.
13. Losina E, Schackman BR, Sadownik SN, et al.. Racial and sex disparities in life expectancy losses among HIV-infected persons in the United States: impact of risk behavior, late initiation, and early discontinuation of antiretroviral therapy. Clin Infect Dis. 2009;49:1570–1578.
14. Jaggy C, von Overbeck J, Ledergerber B, et al.. Mortality in the Swiss HIV Cohort Study (SHCS) and the Swiss general population. Lancet. 2003;362:877–878.
15. van Sighem AI, Gras LA, Reiss P, et al.. Life expectancy of recently diagnosed asymptomatic HIV-infected patients approaches that of uninfected individuals. AIDS. 2010;24:1527–1535.
16. Brinkhof MW, Boulle A, Weigel R, et al.. Mortality of HIV-infected patients starting antiretroviral therapy in sub-Saharan Africa: comparison with HIV-unrelated mortality. PLoS Med. 2009;6:e1000066.
17. UNAIDS. Report on the Global AIDS Epidemic Joint United Nations Programme on HIV/AIDS. Geneva, Switzerland; 2010.
18. Zhang F, Haberer JE, Wang Y, et al.. The Chinese free antiretroviral treatment program: challenges and responses. AIDS. 2007;21(suppl 8):S143–S148.
19. Zhang F, Dou Z, Ma Y, et al.. Five-year outcomes of the China National Free Antiretroviral Treatment Program. Ann Intern Med. 2009;151:241–251, W-252.
20. Dou Z, Chen RY, Wang Z, et al.. HIV-infected former plasma donors in rural Central China: from infection to survival outcomes, 1985-2008. PLoS One. 2010;5:e13737.
21. Ma Y, Zhao D, Yu L, et al.. Predictors of virologic failure in HIV-1-infected adults receiving first-line antiretroviral therapy in 8 provinces in China. Clin Infect Dis. 2010;50:264–271.
22. Zhang F, Dou Z, Ma Y, et al.. Effect of earlier initiation of antiretroviral treatment and increased treatment coverage on HIV-related mortality in China: a national observational cohort study. Lancet Infect Dis. 2009;11:516–524.
23. Zhang FJ, Pan J, Yu L, et al.. Current progress of China's free ART program. Cell Res. 2005;15:877–882.
24. Ma Y, Zhang F, Zhao Y, et al.. Cohort profile: the Chinese national free antiretroviral treatment cohort. Int J Epidemiol. 2009;39:973–979.
25. Zhang F. China Free Antiretroviral Therapy Manual, 2008 Edition. Beijing, China: People's Medical Publishing House Co., LTD; 2008.
27. Hu Y, Zhou M, Wang L, et al.. Analysis on characteristics of death patients in hospital in China, 2006. Dis Surveill. 2008;23:788–791.
28. Rothman K, Greenland S. Modern Epidemiology. 2nd ed. Philadelphia, PA: Lippincott Williams & Wilkins; 1998.
29. Dickman PW, Sloggett A, Hills M, et al.. Regression models for relative survival. Stat Med. 2004;23:51–64.
30. Bhaskaran K, Hamouda O, Sannes M, et al.. Changes in the risk of death after HIV seroconversion compared with mortality in the general population. JAMA. 2008;300:51–59.
31. Zwahlen M, Harris R, May M, et al.. Mortality of HIV-infected patients starting potent antiretroviral therapy: comparison with the general population in nine industrialized countries. Int J Epidemiol. 2009;38:1624–1633.
32. May M, Boulle A, Phiri S, et al.. Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes. Lancet. 2010;376:449–457.
33. Kitahata MM, Gange SJ, Abraham AG, et al.. Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med. 2009;360:1815–1826.
34. Sterne JA, May M, Costagliola D, et al.. Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies. Lancet. 2009;373:1352–1363.
35. Cain LE, Robins JM, Lanoy E, et al.. When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data. Int J Biostat. 2010;6:18.
36. Althoff KN, Gange SJ, Klein MB, et al.. Late presentation for human immunodeficiency virus care in the United States and Canada. Clin Infect Dis. 2010;50:1512–1520.