Title: All-cause mortality in the cohorts of the Spanish AIDS Research Network (RIS) compared with the general population:

Transcription

1 Author's response to reviews Title: All-cause mortality in the cohorts of the Spanish AIDS Research Network (RIS) compared with the general population: Authors: Victoria V Hernando (vhernando@isciii.es) Belen B Alejos (balejos@isciii.es) Sunsana S Monge (smonge@isciii.es) Juan J Berenguer (jbb4@me.com) Lourdes L Anta (lourdes.anta@hotmail.com) David D Vinuesa (vinudav@yahoo.es) Rosario R Palacios (rosariopalacio@gmail.com) Roberto R Muga (rmuga.germanstrias@gencat.cat) Santiago S Moreno (smoreno.hrc@salud.madrid.org) Inma I Jarrin (ijarrin@isciii.es) Version: 3 Date: 5 July 2013 Author's response to reviews: see over

2 MS: All-cause mortality in the cohorts of the Spanish AIDS Research Network (RIS) compared with the general population: Victoria V Hernando, Belen B Alejos, Sunsana S Monge, Juan J Berenguer, Lourdes L Anta, David D Vinuesa, Rosario R Palacios, Roberto R Muga, Santiago S Moreno and Inma I Jarrin Dear Miss Hernando, Your manuscript has now been peer reviewed and the comments are accessible in PDF format from the links below. Do let us know if you have any problems opening the files. Referee 1: Referee 3: Referee 2: Editors Comment: "The authors should revise their manuscript convincingly addressing the issues raised be the reviewers, particularly the requests for major compulsory revisions, before a decision can be taken." Editorial Requirement: --> Please update your ethics statement to include the name of the ethics committee that approved your study within the methods We would be grateful if you could address the comments in a revised manuscript and provide a cover letter giving a point-by-point response to the concerns. Please also ensure that your revised manuscript conforms to the journal style ( ). It is important that your files are correctly formatted. We look forward to receiving your revised manuscript by 5 July If you imagine that it will take longer to prepare please give us some estimate of when we can expect it. You should upload your cover letter and revised manuscript through You will find more detailed instructions at the base of this . Please don't hesitate to contact me if you have any problems or questions regarding your manuscript. With best wishes, Ms. Sheryl Ramos

3 Web: To submit your revised manuscript When you have revised your manuscript in light of the reviewers' comments and made any required changes to the format of your paper, please upload the revised version by following these instructions: 1. Go to and log on with your address and password. 2. With the 'Manuscript details' tab, please update the title, abstract and author details if they have changed since the previous version. It is very important that all changes are updated on this page, as well as in the manuscript file as the information on this page will be used in PubMed and on BioMed Central if your manuscript is accepted for publication. 3. With the 'Cover letter' tab, please provide a covering letter with a point-by-point description of the changes made. 4. With the 'Upload files' tab, please upload the revised version of the manuscript and press 'Submit new version'. Please wait for the confirmation page to appear - this may take a few moments.

4 Authors response to Reviewers Comments Reviewer 1: Andrea De Luca Hernando et al describe the all-cause mortality rates in 2 large Spanish cohorts of HIV infected and illustrate the SMR as compared to the general Spanish population of same sex and age. The main finding of their study is that the mortality rate is still higher than that of the general population, particularly in individuals with a diagnosis of AIDS and in those with positive HCV antibody serostatus. Major compulsory revisions: Several large epodemiological studies have already described similar findings, including a more recent multinacional multicohort study (Collaboration of Observational HIV Epidemiological Research Europe (COHERE) in EuroCoord, Lewden C, Bouteloup V, De Wit S et al. Int J Epidemiol 2012 Apr; 41(2):433-45) that the authors should cite and refer to. The Cohere study shows, in a much large cohort, similar mortality rates and a similar increase in patients with AIDS as CoRIS. Higher mortlity rates were observed in IDU. However Cohere was not able to analyze the effect of HCV infection. The original finding of this study is the relation of an excess mortality with HCV infection. This should be commented in the light of another important paper (Chen TY et al. Clin infect Dis 2009;49: ) highlighting how the excess in mortality due to HCV is not due to accelerated HIV progression but rather to other causes. This should be discussed particularly because CoRIS cannot differentiate among causes of death. Response: We agree with the reviewer and we have added this paper to the references. In the discussion we have added comments to these papers. - Changes in the main text - Discussion, 3 rd paragraph.and Chen et al in a meta-analysis found that the risk of mortality was increased in HCV/HIV coinfected patients in HAART era [15].. Discussion, 4 th paragraph: Others studies observed a lower mortality in recent years with the improvement in antiretroviral therapies [19-22], although when specific groups were analyzed, for example: IDUs, found that mortality risk remain elevated [22]. One major still non-addressed issue in these cohort studies is how much the effect on excess mortality of being current or former IDU and HCV serostatus are independent from each other. Indeed both groups show a similarly elevated SMR. It would be very relevant if the authors could try to address this statistically (eg through Poisson regresssion models using rough mortality rates as the endpoint)(this is a discretionary revision but would be a relevant added value). In any case the authors should comment more extensively on the fact that these could be markers of behaviors that could increase mortality for liver-related or other causes (IV infections, suicide).

5 Similarly, an adjusted analysis could help interpreting the findings on the reduced mortality rates in the more recent of the 2 cohorts: is this an effect of improved ART/care or of the reduction of IDU/HCV? Response: We agree with the reviewer the effects of IDU and HCV seroestatus might be not independent. Following reviewer s suggestions, we have repeated the analysis, calculating SMR adjusted by gender, age, category of transmission and HCV test. These variables are the main predictor factors of high SMR. As reviewer suggested, SMR for IDU and HCV infection has been reduced after adjustment. In the figure 1 the new SMR values are shown. The main text has been modified to shown this new analysis. - Changes in the main text - Methods Statistical Analysis: 3 rd paragraph, 3 rd sentence. SMR were calculated through Poisson models offsetting expected mortality rates, and adjusted for gender, age, category of transmission and HCV test. Results Mortality Rates, Standardized Mortality Ratios and Excess Mortality Rates. 3 rd paragraph Global mortality in both CoRIS cohorts was 6.8 (95% CI: ) times higher than mortality of the general population of same age and sex. As opposed to the crude mortality rates, standardized mortality ratios were higher in women (10.5; 95% CI: ) compared to men (5.6; 95% CI: ). Still, a higher SMR was found for IDUs (9.7; 95% CI: ), persons with an AIDS diagnosis (14.9; 95% CI: ), persons co-infected with HCV (9.2; 95% CI: ) and those receiving antiretroviral treatment (8.1; 95% CI: ). Discussion 4 th paragraph In our study, we found a similar SMR for patients recruited in CoRIS, from 2004 onwards, and those recruited in CoRIS-MD, from 1997 to 2003, after adjustment for gender, age, transmission category and HCV infection. That is, the difference in the subject s characteristics along these years, the decrease in the representation of IDUs and the percentage of HCV co-infected subjects [16-18] were corrected after adjustment. Others studies observed a lower mortality in recent years with the improvement in antiretroviral therapies [19-22], although when specific groups were analyzed, for example: IDUs, found that mortality risk remain elevated [22]. Minor: Page 8 line 3 correct IDU for UDI Response: Granted. We have corrected the mistake

6 Reviewer 2: Ann-Sofi Duberg Title: All-cause mortality in the cohorts of the Spanish AIDS Research Network (RIS) compared with the general population: Authors: Victoria V Hernando, Belen B Alejos, Susana S Monge, Juan J Berenguer, Lourdes L Anta, David D Vinuesa, Rosario R Palacios, Roberto R Muga, Santiago S Moreno, and Inma I Jarrin BMC Infectious Diseases Research article This is a study of mortality in a large cohort of HIV-infected patients naïve to cart at study entry. This cohort has been described before, and mortality compared with the general population was studied in a similar way before, see reference 13. In this new study two more years of follow-up was added, otherwise the study in reference 13 was more complete also studying some specific causes of death. The here presented study is a follow-up without any new hypotheses or questions and no specific causes of death. The study could have been of a higher interest if the authors had waited a few more years to get more information and to study the temporal trends. Response: We agree with the reviewer that more years of follow-up will increase the interest of the paper. We believe that the Uemonstr here presented can be interest and show interesting results. We have included an hypothesis in the introduction and the second paragraph has been changed. - Changes in the main text Introduction, 2 nd paragraph Unlike other cohorts, in this work we have analyzed data of a cohort of persons with HIV infection recruited during a period where cart available is highly effective and all patients are naïve to treatment. But we believe that even though these patients may be in a better starting point than patients in other similar studies, the risk of mortality compared with the general population is still higher. Therefore, the objectives of this study were About the methods there is an issue. There is no discussion about the risk of selection bias resulting in too high standardized mortality ratios. When comparing with mortality or incidences in the general population you may need to exclude a time period of 6 or 12 months after the cohort entry, excluding both observation time and patients with a studied outcome during a lag-time period. A way to study if there is selction bias is to calculate SMR for the first 6 or 12 months after cohort entry separately (for all patients together) and if SMR is higher than the SMR for the whole study period then you have selection bias and should use a lag time. An example is the article: Omland LH, et al. Liver cancer and non-hoghkin lymphoma in hepatitis C-virus infected patients: results from the DANVIR cohort study. Int J Cancer May 15; 130(10): In this study the standardized incidente ratios (SIR) for the first year was much higher than for the following years.

7 In another study Duberg AS et al. Cause if death in individuals with chronic HBV and/or HCV infection, a nationwide community-based register study. J Viral Hepat 2008 Jul; 15(7): A six months lag time was used resulting in an 8% reduction of observation time but a much higher percentage (16-27%) of deaths, indicating selection bias and the need for a lag time. More about this in: Törner A, et al. A proposed method to adjust for selection bias in cohort studies. Am J Epidemiol 2010 Mar 1;171(5): Response: We agree with the reviewer that it is necessary to establish a time window at the time to cohort entry to avoid an overestimation of the risk. In our study, we merged data of the two cohorts. One of the inclusion criteria in CoRIS-MD is that patients had at least 6 months of follow-up. For that, to merge both cohorts, we established this time for all patients. So as, we have not considered patients with time of follow-up less than 6 months, we have deleted individuals who have dead in this period and have not reached six months of follow-up. Following reviewer s suggestion we have performed a sensitivity analysis considering the first 12 months of follow-up, which we have included and discussed in the paper. Next table shows adjusted SMR only considering the first 12 months of follow-up: Table (These data do not show in the manuscript) SMR adjusted (95% CI) Total 4.0 ( ) Gender Age group at cohort entry Category of transmission AIDS CD4 count at cohort entry HIV viral load at cohort entry Cohorts HCV test Males Females >=50 IDUs MSM Heterosexual Others/Unknown No Yes < >=350 Unknown < > Unknown CoRIS ( ) CoRIS-MD ( ) Negative Positive 3.0 ( ) 7.3 ( ) 4.1 ( ) 4.1 ( ) 3.9 ( ) 3.4 ( ) 5.5 ( ) 2.8 ( ) 3.4 ( ) 6.0 ( ) 2.1 ( ) 13.4 ( ) 10.9 ( ) 2.3 ( ) 1.2 ( ) 1.9 ( ) 3.0 ( ) 2.7 ( ) 9.6 ( ) 1.1 ( ) 5.5 ( ) 2.4 ( ) 3.2 ( ) 5.1 ( )

8 Antiretroviral treatment No Yes 1.9 ( ) 6.7 ( ) These results show lower SMRs values than those considering the whole study period. We believe that when we establish as inclusion criteria to have at least 6 months of follow-up, we are introducing a time window to avoid the selection bias indirectly. - Changes in the main text Methods Statistical Analysis: 4 th paragraph A sensitivity analysis was performed to assess a possible selection bias. The SMR was calculated for the first 12 months after cohort entry separately for all patients together. This was to determinate whether it is necessary to include a lag time to avoid an overestimation of SMR. Results Mortality Rates, Standardized Mortality Ratios and Excess Mortality Rates: 4 th paragraph. In the sensitivity analysis, considering only the first 12 month of follow-up, SMR is lower than in the complete analysis (4.0; 95% CI ). Discussion 7 th paragraph The sensitivity analysis shows that when we establish as inclusion criteria to have at least 6 months of follow-up, we are introducing a time window to avoid the selection bias indirectly and overestimate SMRs. 5. Introduction 1a. No actual hypothesis or question is posed but the objectives to compare the mortality in the study population with the general population is well defined. Response: Granted. We have changed the introduction to improve this point. - Changes in the main text Unlike other cohorts, in this work we have analyzed data of a cohort of persons with HIV infection recruited during a period where cart available is highly effective and all patients are naïve to treatment. But we believe that even though these patients may be in a better starting point than patients in other similar studies, the risk of mortality compared with the general population is still higher. Therefore, the objectives of this study were 1b. Introduction, 1 st paragraph, 3 rd sentence: could be revised to clarify, also, instead of at the expense of - don t you mean: achieved thanks to the decreasing AIDSrelated mortality?? Response: We change the sentence.

9 - Changes in the main text Global reduction in mortality has been achieved thanks to the decreasing AIDSrelated mortality Methods, statistical analyses 2a. As mentioned above I think the authors should think the possibility of too high SMR because of selection bias. I recommend them to study (and discuss) if a lag time is needed. Response: Granted. This has been already answered. 3. Results, Baseline characteristics 3a. 1 st paragraph, 2 nd line: 28,743 Response: We have changed it. 3b. 2 nd paragraph, 1 st sentence. And median age at cohort entry was. Response: We have changed this sentence. 3c. 2 nd paragraph, 2 nd, 4 th, 5 th lines tooo many hyphens Response: We hace changed the paragraph. - Changes in the main text Men represented 78.0% (n=6,412) of the sample, and median age at cohort entry was 35.0 years (interquartile range IQR: ), 35.5 years (IQR: ) for men and 34.2 years (IQR: ) for women. Regarding transmission categories, the sample was distributed between injecting drugs users (IDUs) or ex users, 25.0% (n=2,050), men who have sex with men (MSM), 39.6% (n=3,255) and heterosexuals, 30.7% (n=2,524). 3d. 3 rd paragraph, 2 nd sentence, UDI should probably be IDU Response: We have changed this acronym. 3e. Table 1. Age at cohort entry. Also, I would appreciate the number of person years for each strata, and age at cohort entry at least for men and women. Response: Granted. The table 1 has been changed and we have added the personyears in each strata. The medians age at cohort entry for men and women have added in the main text in the results. - Changes in the main text

10 and median age at the cohort entry was 35.0 years (interquartile range IQR: ), 35.5 years (IQR: ) for men and 34.2 years (IQR: ) for women. 4. Results, Mortality Rates, standardized 4a. Figure 1. In my copy there was two figure 1. Response: Granted. We have deleted one figure. 4b. 3 rd paragraph, 1 st line: mortality in both cohorts clarify, I assume SMR 4.8 was for the two cohorts together. Response: Yes, This is the global SMR for all patients analysed. 4c. As you write, crude rates and excess mortality rates are very similar. These results, especially the excess mortality rate is of little value when you don t know the age and the observation time for the different groups. Response: Sorry, but we do not understand what reviewer asks us. Please clarify. 5. Discussion 5a. 5 th paragraph, 2 nd line:... showed a mortality ratio (not rate). Response: We have changed the sentence. 5b. 5 th paragraph, 2 nd sentence: and almost doubles the one of men from the general population? Just exclude, maybe they doubled the one from men in the cohort Response: Granted. We have changed the sentence. - Changes in the main text and almost doubles the one from men in the cohorts. 5c. 5 th paragraph, 3 rd sentence: This higher relative mortality in women could be explained by the fact that the mortality rates in women in the general population is very low between age... Exclude that women has higher life expectancy. It has been Uemonstrated before that young female IDUs have a higher relative risk of dying that men with IDU maybe because of the lower risk in general population women that men or because female IDU are more exposed (?). Response: This is an interesting comment but we would need other approaches to analyze and test that hypothesis. 5d. Please discuss a little more about the probable causes of death. It seems like much of the over-risk is related to IDU. SMR is highest in young people, in IDUs, and in HCVcoinfected (probably IDUs), this ought to be discussed. The very high risk of death from drug use and other external reasons in HCV-infected young drug addicts has been

11 described before and was Uemonstrated in our study Duberg AS, et al. Cause of death in individuals with chronic HBV and/or HCV infection, a nationide community-based register study. J Viral Hepat For those who survived we could later on see an increase in liver-realted and other causes of death. Response: We agree with this comment. For this analysis we have not enough data and sample size to analysis the different causes of death in depth, but we note in the conclusion For future studies, it would be advisable to consider, along with global mortality, excess mortality rate for specific causes of death, such a hepatic or non-aids related malignancies. 5e. Again, I miss the discussion on the possibility of too high SMRs selection bias? Response: Granted. This has been already answered. Major compulsory revisions: the method issue discussed in the beginning and repeated in point 2a and 5e. Minor essential revisions: Points 3c, 3d, 4a, 4b, 5a, 5b, 5d. Discretionary revisions: Points 1a, 1b, 3a, 3b, 3e, 5c.

12 Reviewer 3: Sundhiya Mandalia This is a straightforward study to estimate overall mortality rates, standardized mortality ratios and excess mortality rates of cohorts of the AIDS Research Network (RIS) (Coris-MD and CoRIS) compared to the general population. Authors concluded that mortality among HIV-positive persons remains higher than that of the general population of similar age and sex, with significant differences associated with a history of AIDS or HCV co-infection. Major compulsory revisions: 1) Statistical methods need some clarifications. For instance, there is around 8-10% of information on entry CD4 count, viral load data that were missing. How were these handled? Response: We are aware that it is important to handle missing data correctly. In this analysis we believe that we can used "missing indicator method" to resolve this problem, including an additional category for missing in CD4 count and HIV viral load at entry. On the other hand, if we would like to use multiple imputations we would need to have complete information on those other variables that to predict missing data, and this is not possible in our dataset. Using the multiple imputation method to predict missing value of CD4 cell counts and HIV viral load at entry could introduce another bias in our study since we are not sure we have measured all factors predicting these two variables. 2) There is lack description of modelling SMR s and excess mortality rates, and what method was used to derive 95% confidence intervals (CIs). If these were derived using generalized linear models with Poisson error structure then these need to be described with some level of detail. Response: Granted. We have added more details on statistical methods used to model SMR and to calculate excess mortality rates. - Changes in the main text - Methods section - Statistical analyses 2 nd paragraph.. We calculated mortality rates, overall and according to socio-demographic and clinical characteristics, as the number of deaths by 100 persons-year (py) of follow-up with 95% confidence intervals (95% CI) calculated using the exact Poisson method. 3 rd paragraph, 3 rd sentence. SMR were calculated through Poisson models offsetting expected mortality rates, and adjusted for gender, age, category of transmission and HCV test. 3) Figure 1: It is unclear if data presented in figure 1 are univariate or multivariable model? Results from both univariate and multivariable modeling methods need to be described.

13 Response: The data presented in figure 1 are crude analysis for mortality rates and excess mortality rates and adjusting by gender, age, category of transmission and HCV test for SMRs. 4) Why did the authors choose to study age grouped with 50 years as a cutoff? Did the authors assess age using unbiased age group categorizations and did these figures produce similar SMRs to the 50 years age group categorisation? Response: We have chosen that cutoff because this is the age to discriminate older people within HIV-infected. In others investigations performed (Caro-Murillo AM et al; Blanco JR et al) with CoRIS data about aging and HIV infection have been observed that the age of 50 is a good cutoff to define medically advanced age in HIV-infected people. But to avoid confounding we have changed the age group variable by other with more categories (20-29; 30-39; 40-49; >=50). References: - A.M. Caro-Murillo et al. Infección por el virus de la inmunodeficiencia humana en diferentes grupos de edad: implicaciones potenciales para la prevención, Cohorte CoRIS, España, Med Clin (Barc). 2010;134(12): J.R. Blanco et al. HIV infection and Aging. AIDS Rev. 2010;12: J.R. Blanco et al. Definition of advanced age in HIV infection: looking for an age cut-off. AIDS Res and Human Retroviruses. 2012;28(9): M Greene et al. Management of human immunodeficiency virus infection in advanced age. JAMA 2013;309(13): Changes in the main text - Methods Variables: 1 st paragraph, 1 st line age at cohort entry (20-29; 30-39; 40-49; >=50) 5) These appears to be a significant age, cohort effect presented in Figure 1, however its effect has not been fully explored and described as both variables are presented as covariates. The additive model presented specifies that the influence of age is the same in all time periods and for all cohorts. In fact, however, the influence of age changes over time and across cohorts. In addition the additive model specifies that the influence of conditions in the `present or recent period is the same for people of all ages. Authors are advised to describe these in futher detail. Response: We have recalculated the SMR adjusting by gender, age, category of transmission and HCV to response to the reviewers. We have changed the main text to explain this point. - Changes in the main text - Methods Statistical Analysis: 3 rd paragraph, 3 rd sentence.

14 SMR were calculated through Poisson models offsetting expected mortality rates, and adjusted for gender, age, category of transmission and HCV test. Results Mortality Rates, Standardized Mortality Ratios and Excess Mortality Rates. 3 rd paragraph Global mortality in both CoRIS cohorts was 6.8 (95% CI: ) times higher than mortality of the general population of same age and sex. As opposed to the crude mortality rates, standardized mortality ratios were higher in women (10.5; 95% CI: ) compared to men (5.6; 95% CI: ). Still, a higher SMR was found for IDUs (9.7; 95% CI: ), persons with an AIDS diagnosis (14.9; 95% CI: ), persons co-infected with HCV (9.2; 95% CI: ) and those receiving antiretroviral treatment (8.1; 95% CI: ). Discussion 4 th paragraph In our study, we found a similar SMR for patients recruited in CoRIS, from 2004 onwards, and those recruited in CoRIS-MD, from 1997 to 2003, after adjustment for gender, age, transmission category and HCV infection. That is, the difference in the subject s characteristics along these years, the decrease in the representation of IDUs and the percentage of HCV co-infected subjects [16-18] were corrected after adjustment. Others studies observed a lower mortality in recent years with the improvement in antiretroviral therapies [19-22], although when specific groups were analyzed, for example: IDUs, found that mortality risk remain elevated [22]. Authors may find the following and other suchs article helpful. Jones ME, Swerdlow AJ. Bias in the standardized mortality ratio when using general population rates to estimate expected number of deaths. Am J Epidemiol Nov 15;148(10). Response: We have added a paragraph in the discussion to explain this point as requested by the reviewer. - Changes in the main text - Discussion 6 th paragraph A possible limitation in the calculation of SMR is the use of rate in the general population to calculate the expected deaths, although this population contain also HIV-related deaths. In our analysis, HIV-related mortality represents a small proportion of all-cause mortality in the general population of Spain, so therefore we consider correct to use the general population mortality rates to calculate the mortality rates in a non-hiv infected population. Minor essential revisions: 1) Page 8: Some 60.2% (n=177) were UDI or ex-idu. Please clarify what UDI stand for.

15 Response: Granted. This is a mistake. - Changes in the main text - Some 60.2% (n=177) were IDU or ex-idu.. 2) Page 19: Figure 1: It would be helpful for the reader if the vertical axis for all plots crossed with horizontal axis at 1 to aid the interpretation of 95% CI and thus the significance of the mortality ratios. Response: We thanks the reviewer for his comment but we believe that since we are representing not only SMR but also mortality rates and excess mortality rates, it is more convenient to present vertical axis crossed with horizontal axis at 0. 3) Figure 1 appears twice in the manuscript once on page 19 and repeated on an unnumbered last page Response: Granted. We have deleted one figure. 4) There are a number of typos in the text so authors are advised to check the manuscript carefully. Response: Granted. We have checked all the manuscript. Discretionary revisions: 1) Abstract: It is conventional to write 95% CI rather than CI 95% so authors are advised to amend this. Response: Granted. This has been modified in all documents.