Determinants of loss to care and risk of clinical progression in PLWH who are re-engaged in care after a temporary loss

The risk of developing AIDS is elevated not only among those with a late HIV diagnosis but also among those lost to care (LTC). The aims were to address the risk of becoming LTC and of clinical progression in LTC patients who re-enter care. Patients were defined as LTC if they had no visit for ≥ 18 months. Of these, persons with subsequent visits were defined as re-engaged in care (RIC). Factors associated with becoming LTC and RIC were investigated. The risk of disease progression was estimated by comparing RIC with patients continuously followed. Over 11,285 individuals included, 3962 became LTC, and of these, 1062 were RIC. Older age, presentation with AIDS and with higher HIV-RNA were associated with a reduced risk of LTC. In contrast, lower education level, irregular job, being an immigrant and injecting-drug user were associated with an increased LTC probability. Moreover, RIC with HIV-RNA > 200 copies/mL at the re-entry had a higher risk of clinical progression, while those with HIV-RNA ≤ 200 copies/mL had a higher risk of only non-AIDS progression. Patients re-entering care after being LTC appeared to be at higher risk of clinical progression than those continuously in care. Active strategies for re-engagement in care should be promoted.

www.nature.com/scientificreports/ Temporary versus permanent loss to care may identify a time-dependent definition of "gap in care" or "lost to care". Risk factors associated with a temporary loss to care include younger age, crack/cocaine use, food insecurity, financial and housing instability and phone number changes in the past year, limiting the possibility of re-engaging these individuals 9 .
The ICONA Foundation Study cohort (ICONA) is the largest HIV cohort in Italy and historically has been able to track some key steps of the continuum of care of PLWH, offering a nationally representative picture of HIV care.
The primary aim of this analysis was to describe the risk factors for temporary and permanent loss to care in PLWH enrolled in the ICONA Foundation Study cohort. The secondary aim of the study was to estimate the risk of clinical progression by comparing PLWH retained in care with PLWH who experienced a temporary loss to care and then re-engaged in care.

Results
Out of 16,863 patients enrolled in the Icona Foundation Study cohort over the period January 1997-March 2017 who satisfied the inclusion criteria were included in this analysis (Fig. 1). Overall, 77% were males, and 83% were of Italian origin, with a median age at enrolment of 37 years (Interquartile range, IQR 31-45) (Table 1a). Forty-two percent of the patients were stably employed, 14% were self-employed and 14% were unemployed. In approximately 30% of the study population, the highest level of education achieved was secondary school or lower, while 29% had completed college and 10% had a university degree.
Out of the 11,285 included patients, 3962 (35%) became LTC during follow-up, including 1062 (26.8%) participants who became RIC by re-entering the cohort after a gap in care and 2900 (73.2%) who remained lost to care at the time of this analysis (Table 1b,c). RIC were more frequently female, Italian and employed, they showed a higher proportion of PWID and of HCV co-infected, they showed better virological and immunological parameters at enrolment than LTC patients not returning to the care.
The median time from the date of enrolment in the study to becoming LTC was 13.6 years (95% confidence interval, . The yearly incidence rate of becoming LTC decreased from 1997 to 2005, from 306 per 100 PYFU (95% CI 176-526) to 14.7 (12.2-17.9), with no major changes over the subsequent 10 years, ranging from  per 100 PYFU in 2006 to 18.4 (17.2-19.6) in 2016 ( Fig. 2) (the sample size was too small to provide a precise estimate for 2017).
No longer receiving acƟve follow-up N=2,539 Fewer than two clinical visits recorded in the database, separated by > 90 days N=2,000 Less than 18 months of follow-up N=1,039 N=2,900 definiƟvely lost to follow-up N=1,062 re-engaged in care (RIC) N=3,014 unique paƟents unexposed to gap in care randomly selected to generate 4,248 controls.
The same person could be a control for more than one case. Cases and controls were matched by age, calendar year and length of Ɵme from enrolment to re-engagement in care. www.nature.com/scientificreports/ In multivariable analyses, older age, presentation with AIDS and worse virological and immunological conditions at enrolment were independently associated with a reduced risk of becoming LTC (Table 2a). In contrast, a lower level of education, having an irregular job, being an immigrant and contracting HIV through injecting drugs were factors associated with a higher risk of becoming LTC (Table 2a). No association was found with alcohol and/or drug abuse. The results were similar in a sensitivity analysis in which patients who became RIC were not counted as events (Table 2b). In a separate analysis evaluating the association with HIV-RNA as a  Table 3 describes the main characteristics of the RIC population according to their HIV-RNA level (≤ 200 vs. > 200 copies/mL) at the point of re-entry into care. Individuals who were RIC and had HIV-RNA loads ≤ 200 copies/mL were more likely to be PWID and HCV-Ab-positive, with a lower level of education and with a higher CD4 count at enrolment respect to those with HIV-RNA > 200 copies/mL.
We have also identified factors associated with the probability of re-entering care with HIV-RNA loads > 200 copies/mL among the LTC population. In this analysis, younger age, a higher CD4 count, female sex, a lower level of education, and HCV co-infection were independently associated with a higher chance of achieving the outcome ( Table 4).
The median change in CD4 cell counts in the RIC population with HIV-RNA loads > 200 copies/mL was − 128 cells/µL , and as expected, a longer duration of the gap in care was associated with a larger decrease in the CD4 cell count (Table 5). In contrast, the median change in CD4 cell count in the RIC population with HIV-RNA loads ≤ 200 copies/mL at the time of re-entry was + 62 cell/mmc (IQR − 65, + 202).
After adjusting for the set of chosen confounders (see "Methods" section/footnote of Table 6), RIC status was associated with a significantly higher risk of clinical progression compared to retention in care (Table 6a). Of note, the association was stronger after restricting the analysis to the subset of patients who were RIC who had HIV-RNA loads > 200 copies/mL at the time of re-entering care or patients with unknown HIV-RNA (Table 6a). Similar results were found when performing a sensitivity analysis in which clinical events that occurred within 3 months of the date of re-entry into care were not counted as events (Table 6b). A second sensitivity analysis using a definition of LTC of 12 months also showed similar results (Supplementary Table S1).
When restricting the definition of the outcome to AIDS-related events/death due to AIDS alone, patients who were RIC with HIV-RNA loads > 200 copies/mL had a more than twofold higher risk of developing the endpoint than the unexposed controls (Table 6c). In contrast, patients classified as RIC were at higher risk of serious non-AIDS events or death due to non-AIDS causes than unexposed participants, regardless of the level of HIV-RNA at the time of re-entry (≤ 200 vs. > 200 copies/mL) in the RIC group (Table 6d).

Discussion
Despite the fact that access to HIV care and treatment is universal and free of charge in Italy, there was a significant proportion of patients who met the definition of LTC in our study. www.nature.com/scientificreports/ www.nature.com/scientificreports/ Indeed, more than one-third of the patients in the Icona Foundation study cohort experienced ≥ 1 gap in care from the start of the observational period, with a reduction in gaps in the most recent years. A similar trend has also been described in a meta-analysis of US studies 10 .
Nevertheless, the proportion of PLWH retained in care in our cohort was substantially higher than that observed in the USA, probably because of the differences in health systems between the two countries leading to different situations in the estimated cascade of care 10,11 . Our study showed that the average time to experiencing  Regarding the risk factors for poor retention in care, unsurprisingly, our data showed that those who were LTC had a lower socioeconomic status. The characteristics of patients who were LTC were similar to those described in Table 5. Median value and interquartile range (IQR) of CD4 cell count before and after the gap in care according to gap duration and to HIV-RNA level at re-entry (a) HIV-RNA > 200 copies/mL and (b) HIV-RNA ≤ 200 copies/mL.   Table 6. Crude and adjusted Hazard Ratio (adj HR) and relative 95% confidence interval (CI) of first new clinical event (AIDS/serious non AIDS/hospitalization/death) in the main analysis (a), in the sensitivity analysis (b). Two secondary analyses estimating risk of AIDS event/AIDS-related death (c) and risk of serious non-AIDS event/non-AIDS-related death (d). *Models were adjusted for: gender, risk factor for HIV transmission, Italian nationality, employment status and level of education, and for the following covariates measured at last follow-up before gap in care: HCV-Ab result, CDC C stage, CD4 count and HIV-RNA, presence of psychiatric co-morbidity and alcohol and/or drug abuse. www.nature.com/scientificreports/ previous studies; for example, in the USA, individuals who were LTC were more frequently African Americans, a population with socio-economic status similar to that of immigrants in Italy 13 . It is important to note that having a viral load below 200 copies/mL, a proxy for being on cART, was a protective factor against being lost to care, as was previously described in an analysis of the EuroSIDA data 14 . Inconsistent with the results of other studies 15 , alcohol and/or drug abuse and psychological comorbidities were not found to be associated with the risk of becoming LTC in our analysis.
Reassuringly, the incidence of having a gap in care has been stable in recent years. Of note, as shown in both resource-rich and resource-limited countries, among PLWH at high risk of experiencing such gaps, rapid or same-day cART initiation leads to more favourable outcomes 16 and should be recommended 17 . Nevertheless, the heterogeneity of patients who are typically LTC requires personalized interventions focused on more vulnerable groups, including people who are sceptical of the efficacy of cART 18 . Of note, the majority of person-years of follow-up included in this analysis occurred before the date on which ART initiation regardless of the CD4 count was recommended in the HIV treatment guidelines 17,[19][20][21][22] . Indeed, Italy usually follows the USA guidelines concerning when to start: the national recommendations for starting cART were a CD4 count < 500 cells/µL from June 1998 to 2000, < 350 CD4/µL from 2001 until 2008, < 500 CD4/µL from 2009 until 2012, and then any count from 2012 onwards.
As anticipated, retention in care is a dynamic process. In the ICONA Foundation Study cohort, 27% of the patients who were LTC re-entered care after a mean gap of 2.7 years; 15% died, and 58% were still classified as lost to follow-up at the time of the analysis, possibly having been transferred to another centre outside of the ICONA Network; having moved abroad, as frequently occurs with immigrants, or having died unrecorded.
We cannot rule out that the underestimation of mortality in this group, given that deaths are reported by the treating physicians with no linkage to the regional or national mortality registry. Interestingly, we found that older participants and those with a lower CD4 count at enrolment in the cohort had a reduced probability of re-entering care.
Approximatively half of the population classified as RIC had HIV-RNA loads ≤ 200 copies/mL at the time of re-entry, suggesting that cART was not interrupted and that this group had only missed blood tests and clinical visits but not treatment. The fact that the CD4 count increased on average during the LTC period supports the hypothesis that ART was never stopped in these patients. Mugavero et al. have previously shown that missing a visit was a risk factor for mortality in the USA 4 . In Italy, patients may continue to receive HIV drugs regardless of whether they attend regular medical visits or undergo blood tests, which is different from the situation in the USA. Nevertheless, despite the observed increase in the CD4 count during the gap, which seemed to have protected these patients from the risk of developing AIDS, we still found evidence of a higher risk of serious non-AIDS events in this group. These results are in agreement with those of a recent study conducted in a cohort of PLWH in Ontario, which showed that the mortality risk and the frequency of use of health care resources were higher among those who were lost to follow-up than among participants who were retained in care 12 .
In contrast, people classified as RIC who had HIV-RNA loads > 200 copies/mL at the time of re-entry into care as a consequence of a decrease in the CD4 count during the gap in care had a higher risk of clinical progression, including new AIDS events. On average, the CD4 count decreased by 100 cells/µL during the gap, and the extent of the decrease was proportional to the length of the gap.
After re-entry into care, patient management was frequently clinically challenging, with participants often presenting with difficult-to-treat single or even multiple opportunistic infections, which are associated with a poor prognosis.
Our analysis showed convincing evidence that people classified as RIC had higher risks of AIDS and non-AIDS events than controls, and this was confirmed in a number of sensitivity analyses. Our data also suggest that the negative impact of experiencing a gap in care may still be present years after returning to care, even after re-starting cART. These results are consistent with those of other previous reports. Indeed, detectable HIV-RNA during the gap was shown to have a potential impact on both the individual level with regard to prognoses and at the population level with regard to increasing the risk of HIV transmission 23,24 . In particular, concerning patient outcomes, cumulative exposure to a high viral load has been previously found to be associated with an increased risk of non-AIDS events, such as myocardial infarction and cancers, such as lymphoma [25][26][27] .
Moreover, patients who re-started cART after a gap had slower immune reconstitution than that seen after the first initiation of cART, particularly in those older than 40 years 28,29 .
Our study has some limitations. The observational nature of the study design means that residual confounding cannot be ruled out and that there could be bias in in the comparison of patients who were LTC/RIC with controls. In particular, we have shown that immigrants appeared to be at higher risk of becoming LTC after controlling for a number of potential measured confounders, such as the level of education and type of employment. We cannot rule out the presence of residual confounding due to differences in socio-economic status between foreign-born individuals and Italian individuals that are not fully captured by these variables. Second, our study population was a selected group of people who survived the gap in care and are unlikely to have experienced large drops in their CD4 counts; therefore, it is likely that the risk of developing the outcomes has been underestimated. Additionally, because the analysis was conditioned on events that could occur in the future, we cannot rule out that collider bias might have occurred. Moreover, the incidence of mortality could have been underestimated because Icona data are not linked to regional or national mortality registries. Finally, we used a single definition of LTC, regardless of the HIV-RNA load and CD4 count (which may vary by clinical site), patients' current values of these markers and the time period under observation. However, the results were similar when LTC was defined as an 18-month gap in the main analysis or 12 months in a sensitivity analysis. It was beyond the aim of this analysis to explore strategies to increase retention in HIV care or to evaluate the potential effects of such strategies. www.nature.com/scientificreports/ In conclusion, we report precise estimates of the rate of becoming LTC in a large unselected population of PLWH with access to care in Italy over the period from 1997 to 2017 with a median follow-up period of 5 (2.4-8.8) years. Re-entry into care after a period of > 18 months of being LTC appears to be associated with a higher risk of clinical progression regardless of the HIV-RNA load at the time of re-entry into care. These data emphasize the importance of retention in care with regard to reducing the risk of morbidity and mortality in PLWH. This is particularly important in recent times when HIV care has been disrupted by the COVID-19 pandemic. Our analysis also identified subsets of individuals who are at greater risk of morbidity and mortality if they are lost to care, and these individuals should be prioritized when retention efforts are made. Even if early treatment initiation has decreased the proportion of patients disengaging from care, new strategies should be investigated to obtain higher rates of long-term retention in care, especially for the most vulnerable patients.

Methods
Study cohort. The ICONA Foundation study is a multicentre prospective observational study of HIV-1-in- www.nature.com/scientificreports/ to the gaps in care in this analysis, as it was assumed that they were still receiving care. A detectable viral load at the time of re-entry into care was defined as an HIV-RNA load greater than 200 copies/mL.

Statistical analysis. Predictors of becoming lost to care (LTC) and re-engagement in care (RIC). The Icona
database was frozen for analysis in September 2018. To estimate the incidence of becoming LTC in the cohort, patients' follow-up was calculated from the date of enrolment in the cohort to the date of the last visit prior to the gap in care (regardless of whether they later re-entered care or not, LTC events) or to the last clinical visit in those retained in case (censored). Incidence rates of becoming LTC per calendar year of observation were estimated. These were calculated as the number of individuals lost to care divided by the PYFU in that year and expressed as rates per 100 PYFU, with 95% confidence intervals (CIs).
In the RIC population, the CD4 count and HIV-RNA load measured at the beginning and the end of the gap were considered, and mean changes were compared with paired Student's t-tests. A Cox regression model was used to identify the factors independently associated with the risk of becoming LTC, stratified by clinical centre. The socio-demographic covariates included in the multivariable model were sex, age, nationality (a patient born outside of Italy was considered an immigrant), education level, employment status and route of HIV infection. The clinical covariates included presentation with AIDS, HCV co-infection, HIV-RNA load, CD4 count and calendar year at enrolment. All variables were included in the models as timefixed covariates measured at enrolment. The role of the time-varying HIV-RNA load on the risk of becoming LTC was also separately investigated using a weighting marginal Cox regression model adjusted for nationality, age at enrolment, HIV risk factors and cART initiation. In a separate Cox model, we evaluated an alternative endpoint after excluding LTC patients who subsequently re-engaged in care.
In the LTC group, a logistic regression model was used to identify factors associated with re-entry into care in the subgroup with an HIV-RNA load > 200 copies/mL compared to those who never re-entered care.
All models included all the covariates listed above, selected a priori as potential confounders on the basis of associations previously shown in the literature or axiomatic knowledge, and all models were also adjusted for calendar year of enrolment.
Clinical progression. In the second part of the analysis, we focused on the possible role of a gap in care longer than 18 months with regard to modifying the risk of clinical progression once the person had re-entered care. This question was addressed by comparing the RIC (exposed) population with a control group of unexposed patients who were continuously retained in case. The baseline for the analysis was the date of re-entry into care for cases and the corresponding index date for controls. The index date for controls was after a time from entry that matched the length of time from entry to re-engagement in care of the corresponding patient who became RIC. Two additional matching variables were considered: age [< 30, 30-40, 40-50, > 50 years] and calendar year at enrolment [1997-1998, 1999-2001, 2002-2004, 2005-2007, 2008-2010, 2011-2013, 2014-2017]. Each control could be matched to one or more cases to achieve a ratio of 1:4 between exposed and unexposed individuals.
For each participant, follow-up accrued from baseline to the date of clinical progression/last follow-up visit. Clinical progression was the composite endpoint defined at the time at which a participant first experienced one of the following events: -death due to any cause; -new occurrence of AIDS-related opportunistic infection or neoplasm; -new occurrence of serious non-AIDS-related event; or -new occurrence of hospitalization.
AIDS-related opportunistic infections and neoplasms were defined according to the Centre for Disease Control and Prevention 1993 classification system.
A standard Cox regression model with time-fixed covariates was used to compare the hazard ratio (HR) for experiencing clinical progression in participants with and without gaps in care (RIC population vs matched controls). In a secondary analysis, we divided the RIC population into two groups according to the HIV-RNA load at the time of re-engagement in care (≤ 200 or > 200 copies/mL) and determined the HR for clinical progression by comparing patients with regular follow-up to two groups, namely, the RIC population with HIV-RNA loads ≤ 200 copies/mL and the RIC population with HIV RNA loads > 200 copies/mL at the time of re-engagement in care. Time-fixed covariates included in the multivariable analysis were sex, risk factors for HIV transmission, nationality, employment status and level of education. Again, potential confounders of the association between becoming RIC and the risk of the clinical outcome that were included in the multivariable model were selected a priori on the basis of associations previously shown in the literature or axiomatic knowledge.
The dataset included repeated measurements for HCV-Ab results, CDC C stage, CD4 count and HIV-RNA load, any psychiatric comorbidities and alcohol or drug abuse. All these variables were included in the Cox regression model and included as time-fixed covariates as the value that was recorded at the last visit prior to the gap in care for the RIC group and at on the date of matching for the control group. Of note, this is not the same date that was previously referred to as the 'index date' , which is the date in the unexposed group matching the www.nature.com/scientificreports/ date of re-entry into care in the RIC group. This was done because the values measured at that index date were likely to be a consequence of experiencing the gap in care and not a possible cause and were therefore likely to be mediators rather than potential confounding factors. The proportional hazards assumption was verified by testing the interaction between each of the covariates and the natural logarithm of survival time. All models were stratified by clinical centre.
A sensitivity analysis was performed in which LTC was defined by a gap of > 12 months instead of 18 months. Additionally, as we speculated that the clinical development of symptoms could have been the cause of return to care for many patients, we conducted a sensitivity analysis after ignoring clinical events occurring in the first 3 months after the date of re-engagement in care. Moreover, two further sensitivity analyses were conducted: one counted only AIDS events or deaths due to AIDS and one counted only serious non-AIDS events or non-AIDS-related deaths as outcome.