Log canonical pairs over varieties with maximal Albanese dimension

Let $(X,B)$ be a log canonical pair over a normal variety $Z$ with maximal Albanese dimension. If $K_X+B$ is relatively abundant over $Z$ (for example, $K_X+B$ is relatively big over $Z$), then we prove that $K_X+B$ is abundant. In particular, the subadditvity of Kodaira dimensions $\kappa(K_X+B) \geq \kappa(K_F+B_F)+ \kappa(Z)$ holds, where $F$ is a general fiber, $K_F+B_F= (K_X+B)|_F$, and $\kappa(Z)$ means the Kodaira dimension of a smooth model of $Z$. We discuss several variants of this result in Section 4. We also give a remark on the log Iitaka conjecture for log canonical pairs in Section 5.Comment: 24 pages. Some typos fixe

Virologic and immunologic outcomes of treatment with integrase inhibitors in a real-world setting: The RESPOND cohort consortium

Objectives: To compare virologic and immunologic outcomes of integrase inhibitor (INSTI)-containing, contemporary boosted protease inhibitor (PI/b)-containing and non-nucleotide reverse transcriptase inhibitor (NNRTI)-containing regimens in a real-life setting. Methods: Using logistic regression, virologic and immunologic outcomes of INSTI use were compared to outcomes of PI/b or NNRTI treatment 12 months after treatment start or switch, for participants in the RESPOND cohort consortium. A composite treatment outcome (cTO) was used, defining success as viral load (VL) <200 copies/mL and failure as at least one of: VL ≥200 copies/mL, unknown VL in the time window, any changes of antiretroviral therapy (ART) regimen, AIDS, or death. In addition, on-treatment analysis including only individuals with known VL and no regimen changes was performed. Favorable immunologic response was defined as a 25% increase in CD4 count or as reaching ≥750 CD4 cells/μL. Results: Between January 2012 and January 2019, 13,703 (33.0% ART-naïve) individuals were included, of whom 7,147 started/switched to a regimen with an INSTI, 3,102 to a PI/b and 3,454 to an NNRTI-containing regimen. The main reason for cTO failure in all treatment groups were changes in ART regimen. Compared to INSTIs, the adjusted odds ratio (aOR) of cTO success was significantly lower for PI/b (0.74 [95% confidence interval, CI 0.67–0.82], p <0.001), but similar for NNRTIs (1.07 [CI 0.97–1.17], p = 0.11). On-treatment analysis and sensitivity analyses using a VL cut-off of 50 copies/mL were consistent. Compared to INSTIs, the aORs of a 25% increase in CD4 count were lower for NNRTIs (0.80 [CI 0.71–0.91], p<0.001) and PI/b (0.87 [CI 0.76–0.99], p = 0.04). Conclusion: In this large analysis of a real-world population, cTO and on-treatment success were similar between INSTIs and NNRTIs, but lower for PI/b, though residual confounding cannot be fully excluded. Obtaining favorable immunologic outcomes were more likely for INSTIs than the other drug classes

Integrase Strand Transfer Inhibitor Use and Cancer Incidence in a Large Cohort Setting

Background: Limited data exist examining the association between incident cancer and cumulative integrase inhibitor (INSTI) exposure. Methods: Participants were followed from baseline (latest of local cohort enrollment or January 1, 2012) until the earliest of first cancer, final follow-up, or December 31, 2019. Negative binomial regression was used to assess associations between cancer incidence and time-updated cumulative INSTI exposure, lagged by 6 months. Results: Of 29 340 individuals, 74% were male, 24% were antiretroviral treatment (ART)-naive, and median baseline age was 44 years (interquartile range [IQR], 36-51). Overall, 13 950 (48%) individuals started an INSTI during follow-up. During 160 657 person-years of follow-up ([PYFU] median 6.2; IQR, 3.9-7.5), there were 1078 cancers (incidence rate [IR] 6.7/1000 PYFU; 95% confidence interval [CI], 6.3-7.1). The commonest cancers were non-Hodgkin lymphoma (n=113), lung cancer (112), Kaposi's sarcoma (106), and anal cancer (103). After adjusting for potential confounders, there was no association between cancer risk and INSTI exposure (≤6 months vs no exposure IR ratio: 1.15 [95% CI, 0.89-1.49], &gt;6-12 months; 0.97 [95% CI, 0.71-1.32], &gt;12-24 months; 0.84 [95% CI, 0.64-1.11], &gt;24-36 months; 1.10 [95% CI, 0.82-1.47], &gt;36 months; 0.90 [95% CI, 0.65-1.26] [P=.60]). In ART-naive participants, cancer incidence decreased with increasing INSTI exposure, mainly driven by a decreasing incidence of acquired immune deficiency syndrome cancers; however, there was no association between INSTI exposure and cancer for those ART-experienced (interaction P&lt;.0001). Conclusions: Cancer incidence in each INSTI exposure group was similar, despite relatively wide CIs, providing reassuring early findings that increasing INSTI exposure is unlikely to be associated with an increased cancer risk, although longer follow-up is needed to confirm this finding

Contemporary antiretrovirals and body-mass index: a prospective study of the RESPOND cohort consortium

BACKGROUND: Weight gain effects of individual antiretroviral drugs are not fully understood. We investigated associations between a prespecified clinically significant increase (>7%) in body-mass index (BMI) and contemporary antiretroviral use. METHODS: The International Cohort Consortium of Infectious Diseases (RESPOND) is a prospective, multicohort collaboration, including data from 17 well established cohorts and over 29 000 people living with HIV. People with HIV under prospective follow-up from Jan 1, 2012, and older than 18 years were eligible for inclusion. Each cohort contributed a predefined minimum number of participants related to the size of the specific cohort (with a minimum of 1000 participants). Participants were required to have CD4 cell counts and HIV viral load measurement in the 12 months before or within 3 months after baseline. For all antiretroviral drugs received at or after RESPOND entry, changes from pre-antiretroviral BMI levels (baseline) were considered at each BMI measurement during antiretroviral treatment. We used logistic regression to identify individual antiretrovirals that were associated with first occurrence of a more than 7% increase in BMI from pre-antiretroviral BMI. We adjusted analyses for time on antiretrovirals, pre-antiretroviral BMI, demographics, geographical region, CD4 cell count, viral load, smoking status, and AIDS at baseline. RESULTS: 14 703 people were included in this study, of whom 7863 (53·5%) had a more than 7% increase in BMI. Compared with lamivudine, use of dolutegravir (odds ratio [OR] 1·27, 95% CI 1·17-1·38), raltegravir (1·37, 1·20-1·56), and tenofovir alafenamide (1·38, 1·22-1·35) was significantly associated with a more than 7% BMI increase, as was low pre-antiretroviral BMI (2·10, 1·91-2·31 for underweight vs healthy weight) and Black ethnicity (1·61, 1·47-1·76 vs White ethnicity). Higher CD4 count was associated with a reduced risk of BMI increase (0·97, 0·96-0·98 per 100 cells per μL increase). Relative to lamivudine, dolutegravir without tenofovir alafenamide (OR 1·21, 95% CI 1·19-1·32) and tenofovir alafenamide without dolutegravir (1·33, 1·15-1·53) remained independently associated with a more than 7% increase in BMI; the associations were higher when dolutegravir and tenofovir alafenamide were used concomitantly (1·79, 1·52-2·11, and 1·70, 1·44-2·01, respectively). INTERPRETATION: Clinicians and people with HIV should be aware of associations between weight gain and use of dolutegravir, tenofovir alafenamide, and raltegravir, particularly given the potential consequences of weight gain, such as insulin resistance, dyslipidaemia, and hypertension. FUNDING: The CHU St Pierre Brussels HIV Cohort, The Austrian HIV Cohort Study, The Australian HIV Observational Database, The AIDS Therapy Evaluation in the Netherlands national observational HIV cohort, The EuroSIDA cohort, The Frankfurt HIV Cohort Study, The Georgian National AIDS Health Information System, The Nice HIV Cohort, The ICONA Foundation, The Modena HIV Cohort, The PISCIS Cohort Study, The Swiss HIV Cohort Study, The Swedish InfCare HIV Cohort, The Royal Free HIV Cohort Study, The San Raffaele Scientific Institute, The University Hospital Bonn HIV Cohort and The University of Cologne HIV Cohorts, ViiV Healthcare, and Gilead Sciences

Clinical Outcomes of 2-Drug Regimens vs 3-Drug Regimens in Antiretroviral Treatment–Experienced People Living With Human Immunodeficiency Virus

BACKGROUND: Limited data exist comparing clinical outcomes of two-drug regimens (2DRs) and three-drug regimens (3DRs) in people living with HIV. METHODS: Antiretroviral treatment-experienced individuals in RESPOND switching to a new 2DR or 3DR from 1/1/12-1/10/18 were included. The incidence of clinical events (AIDS, non-AIDS cancer, cardiovascular disease, end-stage liver and renal disease, death) was compared between regimens using Poisson regression. RESULTS: Of 9791 individuals included, 1088 (11.1%) started 2DRs and 8703 (88.9%) 3DRs. The most common 2DRs were dolutegravir plus lamivudine (22.8%) and raltegravir plus boosted darunavir (19.8%); the most common 3DR was dolutegravir plus 2 nucleoside reverse transcriptase inhibitors (46.9%). Individuals on 2DRs were older (median 52.6 years [interquartile range 46.7-59.0] vs 47.7 [39.7-54.3]), and a higher proportion had ≥1 comorbidity (81.6% vs 73.9%).There were 619 events during 27,159 person-years of follow-up (PYFU): 540 (incidence rate [IR] 22.5/1000 PYFU [95% CI 20.7-24.5]) on 3DRs, 79 (30.9/1000 PYFU [24.8-38.5]) on 2DRs. The most common events were death (7.5/1000 PYFU [95% CI 6.5-8.6]) and non-AIDS cancer (5.8/1000 PYFU [4.9-6.8]). After adjustment for baseline demographic and clinical characteristics, there was a similar incidence of events on both regimen types (2DRs vs 3DRs IR ratio: 0.92 [0.72-1.19]; p=0.53). CONCLUSIONS: This is the first large, international cohort assessing clinical outcomes on 2DRs. After accounting for baseline characteristics, there was a similar incidence of events on 2DRs and 3DRs. 2DRs appear to be a viable treatment option with regard to clinical outcomes; further research on resistance barriers and long-term durability of 2DRs is needed

Showing no significant difference in plasma IP-10 levels in samples derived from baseline and at 6 months follow-up.

<p>Showing no significant difference in plasma IP-10 levels in samples derived from baseline and at 6 months follow-up.</p

Baseline characteristics for study patients.

<p>Baseline characteristics for study patients.</p

Linear regression showing correlation between HCV-RNA Concentrations in plasma and DBS samples.

<p>Linear regression showing correlation between HCV-RNA Concentrations in plasma and DBS samples.</p

Median plasma IP-10 concentrations at baseline in relation to genotype, ALT levels, TE-score levels- and dynamics and plasma HCV-RNA concentration.

<p>Median plasma IP-10 concentrations at baseline in relation to genotype, ALT levels, TE-score levels- and dynamics and plasma HCV-RNA concentration.</p

Uptake and effectiveness of two-drug compared with three-drug antiretroviral regimens among HIV-positive individuals in Europe.

To access publisher's full text version of this article click on the hyperlink belowObjective: To assess the use of two-drug antiretroviral regimens (2DR) and virologic and immunologic outcomes compared with three-drug regimens (3DR) in the EuroSIDA cohort. Design: Multicentre, prospective cohort study. Methods: Logistic regression was used to analyse the uptake and outcomes among HIV-positive individuals who started or switched to a 2DR compared with those on a 3DR. Virologic outcomes were assessed on-treatment as the proportion of individuals with controlled viral load (<400 copies/ml), or with a composite modified FDA snapshot endpoint (mFDA), with mFDA success defined as controlled viral load at 6 months or 12 months for individuals with a known viral load, no regimen changes, AIDS or death. Immunologic response was defined as a 100 cells/μl or a 25% increase in CD4 cell counts from baseline. Results: Between 1 July 2010 and 31 December 2016, 423 individuals started or switched to a 2DR (eight antiretroviral-naive) and 4347 started a 3DR (566 naive). Individuals on 2DR tended to have suppressed viral load, higher CD4 cell counts and more comorbidities at baseline compared with those on 3DR. There were no differences in the proportions of individuals who obtained on-treatment or mFDA success, and no significant differences in the adjusted odds ratios for mFDA success or immunologic responses between the 2DR and 3DR groups at 6 months or 12 months. Conclusion: In routine clinical practice, 2DR were largely used for virologically suppressed individuals with higher cumulative exposure to antiretrovirals and comorbidities. Virologic and immunologic outcomes were similar among those on 2DR or 3DR, although confounding by indication cannot be fully excluded due to the observational nature of the study