Mercury accumulation has been proposed as a toxic factor that causes neurodegenerative diseases. However, the hazardous health effects of gaseous elemental mercury exposure on the spinal cord in volcanic areas have not been reported previously in the literature. To evaluate the presence of volcanogenic inorganic mercury in the spinal cord, a study was carried out in São Miguel island  by comparing the spinal cord of mice exposed chronically to an active volcanic environment (Furnas village) with individuals not exposed (Rabo de Peixe village), through the autometallographic silver enhancement histochemical method. Moreover, a morphometric and quantification analysis of the axons was carried out. Results exhibited mercury deposits at the lumbar level of the spinal cord in the specimens captured at the site with volcanic activity (Furnas village). A decrease in axon calibre and axonal atrophy was also observed in these specimens. Given that these are relevant hallmarks in the neurodegenerative pathologies, our results highlight the importance of the surveillance of the health of populations chronically exposed to active volcanic environments. Heavy metals occur naturally in the environment from geogenic or anthropogenic sources. Weathering of metal-bearing rocks and volcanic eruptions is natural sources of heavy metals. On the other hand, the anthropogenic share of heavy metals in the environment has increased due to the global level of industrialization and urbanization .2), sulphuric acid (H2SO4), hydrogen sulphide (H2S), hydrogen chloride (HCl), hydrogen fluoride (HF), carbon dioxide (CO2) and the radioactive gas radon (Rn), in addition to heavy metals, such as arsenic (As), mercury (Hg), aluminium (Al), rubidium (Rb), lead (Pb), magnesium (Mg), copper (Cu) and zinc (Zn) [Volcanoes and geothermal areas are associated with emissions of a variety of gases, such as sulphur dioxide SO, sulphurinc (Zn) . Even inacid H2SO, hydrogeinc (Zn) –7. In thinc (Zn) –10, Miyainc (Zn) , 12, Hawinc (Zn) , Icelandinc (Zn)  and New inc (Zn) .In general, heavy metals include essential metals, that are relevant for normal biological functioning, and non-essential metals (e.g. Hg). An inadequate concentration of any of them can alter normal biological functions and cause different cellular stress responses, producing reactive oxygen species and altering the structure and function of proteins . This ce0), inorganic mercury compounds and organic mercury compounds. The different forms of mercury often determine the route of exposure, absorption, distribution and toxicity to target organs. It is released into the environment by volcanic eruptions or human activities. Volcanic eruptions can increase the atmospheric source of mercury by 4–6 times [Mercury is considered one of the main hazardous environmental pollutants since it circulates widely in ecosystems and is not eliminated by the environment. Mercury toxicity and its neurodegenerative effects have been confirmed in several studies . Chemica–6 times . Natural–6 times .2 per day through soil degassing [The Azores archipelago  has nine volcanic islands, some of which with active volcanism. Volcanic activity is marked by soil degassing, carbon dioxide springs and fumarolic fields. The largest of the islands, São Miguel, has three major active volcanoes: Sete Cidades, Fogo and Furnas. The Furnas volcano is estimated to release approximately 968 tons of COegassing .0) in Furnas hydrothermal areas is 9.6 × 10−5 t d−1, for a study area of 0.04 km2; nevertheless, according to these authors, these values are below WHO’s threshold. Amaral et al. [−1 dry wt, respectively).In addition to gases, the volcanic environment of Furnas releases several toxic metals that are bioavailable for both animals and humans. Bagnato et al.  estimatel et al.  found thl et al.  reportedIt is important to note that in the case of a spatially localized threat, such as volcanoes, the physical proximity of a population to the source of the hazard is a key component of vulnerability. According to research published by Freire et al. , more thConsidering all the above, in this study, we compared the presence of volcanogenic inorganic mercury in the spinal cord (in white and grey matter and vascular tissue) of mice chronically exposed to an active volcanic environment (Furnas village) with individuals not exposed (Rabo de Peixe village). The presence of volcanogenic inorganic mercury in the spinal cord of mice was determined by the autometallographic silver enhancement histochemical method. A quantification and a morphometric analysis of the ventral horn axons (axon size and roundness) were also carried out in both groups.Mus musculus since it is found in active and inactive volcanic environments and shares the habitat with humans. Two separate groups of mice were caught alive in two different areas on São Miguel Island: a volcanically active site, Furnas village, and a reference site, Rabo de Peixe village. Rabo de Peixe (with 8000 inhabitants) is a village that does not present any types of volcanic manifestations since the seventieth century [This study was carried, as in previous studies , 27, usi century  and, als century , 22, 29.N = 7; Rabo de Peixe, N = 7) were captured alive using traps located in human-inhabited houses at both locations as it was carried out by Navarro-Sempere et al. [Fourteen mice . All procedures were performed conformed with the recommendations of the European Convention for the Protection of Vertebrate Animals used for Experimental and Other Scientific Purposes (ETS 123), directive 2010/63EU and Portuguese law decree (DL 113/2013).N = 4; Rabo de Peixe, N = 4) was embedded in paraffin, and tissue blocks were sectioned on the microtome Microm HM 340 E  at 4 μm. Serial sections were mounted on gelatinized slides.The spinal cord of eight individuals  procedure was described by Danscher and Moller-Madsen . BrieflyN = 3; Rabo de Peixe, N = 3) was postfixed in 1% osmium tetroxide for 1 h, washed three times in 0.1 M phosphate buffer, dehydrated in a graded series of alcohol and embedded in Epon 812 . Transverse sections, 0.5 μm thick, were cut using a glass knife on a Leica LKB-III ultramicrotome  and stained with 1% toluidine blue.The spinal cord of six mice  were captured using a Lumenera Infinity microscope camera  mounted on a Leica DMRB light microscope using 100 × objective. A region of interest (ROI), with 2000 μm2  or non-circularity of each axon was derived from the axoplasm perimeter and area, as described by Stankovic [For morphometric analysis, three images of ventral horn axons from each animal , except for the weight and age of the animals, for which we have used the SPSS Statistics V. 25.0 software .Statistical analysis was performed by Student’s t (6) =  − 0.411, P = 0.695 (Student’s t-test). The mean (± SE) weight (in grams) was 14.96 ± 1.44 for Furnas village mice and 15.78 ± 0.95 for Rabo de Peixe mice: t (6) =  − 0.475, P = 0.652 (Student’s t-test).The samples used for the AMG did not show statistical differences in either age or weight between the studied groups. The average (± SE) age (in days) of mice was 229 ± 19 in Furnas village and 238 ± 13 in Rabo de Peixe: t (4) = 0.469, P = 0.663 (Student’s t-test). The mean (± SE) weight (in grams) was 13.65 ± 1.5 in Furnas village and 12.74 ± 1.24 for Rabo de Peixe mice: t (4) = 0.465, P = 0.666 (Student’s t-test).Similarly, when comparing the individuals used for the morphometric analyses, there were no significant differences between the 2 groups in terms of age or weight. The mean (± SE) age (in days) was 211 ± 20 in Furnas village and 201 ± 1 in Rabo de Peixe: Black grains were found in both grey and white matter of the spinal cord of those individuals chronically exposed to volcanic environment. By contrast, the mice living in Rabo de Peixe did not show AMG staining compatible with mercury deposits. In the white matter of Furnas mice, a disperse scattered pattern of the black grains can be observed Fig. . For thiAs in the white matter, a scattered stain pattern was found in the endothelium of the ventral fissure vein in animals exposed to the volcanic environment, but no deposits were present in the rodents from the reference site Fig. .Fig. 3A p = 0.693 (Student’s t-test).In the ventral horn of the spinal cord, no significant differences were found in the mean (± SD) axon number between the two groups: 344.67 ± 62.3 in Furnas and 322.56 ± 49 in Rabo de Peixe group; At the light microscopic level, the myelinated axons from the two sites were varied in diameter and shape. In addition, some myelinated axons of Furnas mice showed a greater degree of crenation Fig. . It is ip < 0.005 (Wilcoxon Mann–Whitney test).Furnas animals showed a significant decrease in axons mean (± SD) diameter (1.55 ± 1.2 μm) compared with those caught in Rabo de Peixe (1.69 ± 1.3 μm), Also, we tested for the presence of site differences in the distribution of axons with various diameters. Figure p < 0.005 (Wilcoxon Mann–Whitney test). Concerning larger axon calibre, both groups presented a small proportion: 5.72% in the exposed rodents and 7.72% in the animals caught in Rabo de Peixe. No significant differences were observed in the axon calibre being greater than 4 μm: 5.09 ± 0.98 μm in the Furnas animals and 5.11 ± 0.98 μm in those of Rabo de Peixe, p = 0.619 (Wilcoxon Mann–Whitney test).Following Stankovic , axons wR). Significant differences were observed in the mean (± SD) of the roundness factor between the two studied groups: 1.37 ± 0.36 in the axons from Furnas animals and 1.34 ± 0.35 in the rodents from Rabo de Peixe, p < 0.005 (Wilcoxon Mann–Whitney test). Considering that a circular shape implies a roundness factor between 1 and 1.5, a greater proportion of axons with a R value similar to a circular shape was observed in Rabo de Peixe animals, 77.67%, than in Furnas animals, 73.38%. These data indicate that exposed individuals to the volcanic environment have axons undergone more atrophic changes.Another morphological parameter analyzed was the roundness factor , after inhalation and lung uptake [0 is the lung and, even at very low concentrations in the environment, the chronic exposure to gaseous mercury results in its bioaccumulation in the lung tissue. Once inhaled, Hg0 enters the bloodstream, reaching the skeletal muscle and the motor neurons. The Hg0 can be oxidized to Hg++, mercuric mercury considered the toxic form, by the catalase-hydrogen peroxide pathway [0 can cross the blood–brain barrier [It is known that active neurons are inclined to take up more circulating toxicants , so we hg uptake , arrivesg uptake , the mai pathway –47 insid pathway . Therefo pathway  on the i pathway . Moreove barrier , 47, 49,The inorganic mercury has been described as an important environmental factor in the pathogenesis of sporadic motor neuron diseases (SMND), including amyotrophic lateral sclerosis (ALS)  which isAs mentioned above, mercury transport inside the nerve cells could be due to retrograde axonal transport. In this transport phase, heavy metals generate free radicals, which could cause structural damage to neurofilaments through oxidative stress mechanisms. It should be noted that the CNS is very vulnerable to reactive oxygen species and other free radicals. As proposed in the study of Griffin and Watson , there iOn the other hand, the role of microtubules must be considered since it has been reported that elemental mercury can act as a toxicant also affecting microtubules . It has In previous studies carried out in the same location in the Azores archipelago, mice living in volcanic environments showed mercury deposits in different locations of the brain , as wellNevertheless, given the complexity of the volcanic environment, several other toxic elements, such as gases and metals, may also contribute to enhancing the development of neural damage since some of these toxic elements may enter the body mainly by inhalation and reach the bloodstream and the CNS. To overcome these limitations, laboratorial essays need to be further developed in order to test the effects of the exposure of genetically controlled animals to each of the main contaminants present in the volcanic environment.Overall, these findings support our previous studies about mercury uptake in the CNS. Moreover, we demonstrated changes in axonal calibre and the presence of crenated axons in the mice from Furnas village. Since exposure to mercury and axonal atrophy are risk factors for SMND, we recommend the health surveillance of populations chronically exposed to active volcanic environments.Finally, it would be important to be able to perform studies in humans since observing any pathological signs of neurodegenerative diseases related to mercury accumulation in mice are very difficult due to their short lifespan.


Conditional cash transfers (CTs) augmented with other interventions are promising interventions for reducing HIV risk in adolescent girls and young women.A multi‐phase, quasi‐experimental study assessed the impact of a CT  conditional on attending a skills building intervention, Women of Worth (WoW), designed to improve sexual and reproductive health (SRH) outcomes in Cape Town, South Africa from May 2017 to December 2019. The intervention entailed 12 sessions with encouragement to attend adolescent and youth‐friendly health services. Women aged 19–24 years were randomized 1:1 to receive the intervention with a CT (“cash + care” or C+C) or without a CT (“care”). The study included a pilot phase followed by a post‐modification phase with improved uptake and retention without changing programme content or CT. Self‐reported HIV prevalence and SRH/HIV vulnerability were assessed via a self‐administered questionnaire at baseline, after 11 sessions, and 6–30 months’ post‐intervention for a subset. Mixed effect logistic regression models were fitted to estimate within‐subject changes in outcomes.p <0.001). Three‐hundred and thirty women were followed for a median of 15.0 months  to assess the durability of impact. Self‐reported new employment status increased more than three‐fold (p <0.001) at WoW completion and was sustained to the longer time point. Intimate partner violence indicators were reduced immediately after WoW, but this was not durable.Of 5116 participants, 904 (452 participants per arm) were in the pilot and 4212 (2039 “care” participants and 2173 “C+C” participants) were in the post modified phase. There were 1867 (85.9%) and 135  participants in the “C+C” group and the “Care,” respectively, that were WoW completers (≥ 11 sessions/retention). During the pilot phase, 194 (42.9%) and 18 (4.0%) participants in “C+C” and the “care” groups were retained. Receiving a CT sustained participation nearly 60‐fold (OR 60.37; 95% CI: 17.32; 210.50, Participants receiving CT had sustained participation in an SRH/HIV prevention skills building with improvement in employment and some SRH outcomes. Layered, “young woman centred” programmes to address HIV and SRH risk in young women may be enhanced with CT. Half ofThe complexity of HIV vulnerability in young women has led to calls for multi‐deterministic approaches that combine behavioural and structural interventions delivered close to where they live , 13, 14.A multi‐phase, quasi‐experimental study, Women of Worth (WoW), was conducted among 19‐ to 24‐year‐old women in Cape Town, SA as a component of an integrated, multi‐component, multi‐sector intervention for young people (aged 10–24 years) funded by the Global Fund for Malaria, HIV and TB . We hypo22.1The study was conducted across two sub‐districts in Cape Town, SA, with a combined population of approximately 1 million living in formal and informal urban settlements. This setting is characterized by high levels of HIV, crime, violence and socio‐economic deprivation , 23. Mos2.2Approximately 10,000 19‐ to 24‐year‐old women were recruited from the study area, regardless of HIV status. Inclusion criteria included residing in the study area and owning a mobile phone or having access to one. The latter facilitated CT payment. Recruitment was done through social media, word of mouth and community‐based organizations.2.3The WoW program was adapted from a pilot intervention, GirlPower, implemented in SA and Malawi between 2016 and 2017 . The facWe used a multi‐phase, quasi‐experimental mixed‐methods study design. Participants registered on‐site by self‐selection on a first‐come, first‐served basis by providing electronic informed consent and self‐administering an SRH/HIV risk assessment questionnaire. Questionnaires were conducted at baseline (registration) and following the 11th session.In the initial randomized control trial (RCT) phase, approximately 5000 participants were randomized 1:1 to “care” arm versus “C+C” arm. After enrolling approximately 1000 participants in the pilot phase, low participant retention prompted a study pause between December 2017 and March 2018. The RE‐AIM approach was used to review the program and distil modifications solicited from staff and participant consultations shown in Table 2.4Self‐administered questionnaire data and session attendance were collected on a digital tablet using a fingerprint‐enabled biometric information system. After registration, participants were assigned a unique participant identification number (PID). PIDs were randomly assigned to a study arm following a biometric check‐in and out at the first session. A message indicating arm assignment was automatically sent to participant's mobile phone. A digital voucher was sent after each session attendance via mobile phone to those randomized to the “C+C” arm. Participants in the “care” arm received a message of encouragement but no voucher.2.5p ≤ 0.05 threshold for statistical significance. As a measure of retention, WoW completers were defined as those who completed at least 11 sessions. We fitted logistic regression models with subject‐specific random for mixed effects, to estimate the intra‐individual change estimates of effect. We measured changes in self‐reported HIV, behavioural and structural SRH risks from baseline to (1) end of WoW and (2) at follow up (6–30 months post‐exposure) irrespective of WoW completion. Observations in the models included subjects at baseline and at these outer time points. Maximum‐likelihood estimation of the model parameters ensured unbiased estimates despite loss to follow up (LTFU) under the missing‐at‐random assumption. However, to mitigate potential bias due to unmeasured confounders or predictors of LTFU in the “care” arm, we analysed change in outcomes not disaggregated by study arm. Models included the number of visits attended to measure intervention dose. Models were adjusted for confounding variables that were (1) statistically different at baseline between the study arms and (2) baseline variables that were associated with LTFU at the end of WoW and at follow up  HREC 033/2017 and HREC 716/2018. The trial is registered with BMC Trials ISRCTN25016009 33.1Program participation is shown in Figure 3.2Table 3.3p <0.001). We saw a 23‐fold improvement in retention of participants in the post modification phase  versus the pilot phase. Baseline variables associated with LTFU (Table Two thousand and two hundred and fourteen 43.3%) completed the programme, with significant differences in retention between study arms and phases Figure . Of “C+C.3% complFU Table  and S2b 3.4Of the 2214 “WoW completers,” 1149 (51.9%) completed questionnaires after 11 sessions: 1005 “C+C” and 144 “care.” Overall, the “C+C” and “care” groups completed the programme in a similar duration of median 15 weeks (IQR: 12 weeks) and 14 weeks (IQR: 12 weeks), respectively. The post modification phase had a similar completion time between arms of median 14 weeks with a shorter IQR of 7 weeks. Participants who enrolled during the pilot phase had a longer completion time of median 46 weeks (IQR: 33 weeks).p <0.001) and self‐reporting facility satisfaction increased 45% (p <0.001). The odds of self‐reporting GBV threat, forced sex and transactional sex were reduced by 47% (p <0.001), 63% (p <0. 001) and 50% (p <0.001), respectively.Adjusted changes in self‐reported SRH behavioural and structural risk factors immediately after WoW with both study arms combined are shown in Table p < 0.001) and 50% (p< 0.001), respectively, at the end of WoW compared to baseline. However, comparing the same period, the odds of self‐reporting HIV testing in the last 6 months, condom use at last sex and recognition of HIV risk perception were reduced by 75% (p <0.001), 51% (p< 0.001) and 95% (p < 0.001), respectively. In addition to the 290 participants who self‐reported HIV positivity at baseline, 42 participants at the end of WoW and seven participants at follow up self‐reported HIV positivity for the first time. These numbers were insufficient to model and assess new HIV infection.The changes on SRH behavioural risk factors were mixed. The odds of self‐reporting uptake of contraception and STI treatment increased by 62% (3.5p <0.001) compared to baseline (Table There were 330 participants (132 “care” and 198 “C+C”) of the 1000 participants invited to test for durability of effect and the dose response of the skills building sessions who were in the randomized phases of the study. They had follow‐up time of median 15.0 months  post‐intervention. In this group, 206 (62.4%) attended ≥9 sessions and 102 (30.9%) ≤ 3 sessions. At this time point, the odds of self‐reported current employment status showed durability and were increased 2.5‐fold (4Receipt of a modest CT increased young women's sustained participation in the WoW SRH skills building programme by 60‐fold. Finding and holding participant attention in such programs, especially in the context of competing priorities, is difficult. Young women who have recently completed secondary school are highly transient and difficult to retain, as illustrated by the limited number who could be located for long‐term follow up. Yet, SRH impact depends on sufficient session exposure, making session attendance critical , 27, 28.Baseline characteristics demonstrated low socio‐economic profiles with high rates of unemployment and HIV prevalence and risk behaviours, similar to population characteristics in the study areas . Youth cCurbing unemployment addresses a structural determinant of HIV vulnerability in AGYW and a sustainable development priority , 33. UneOur findings on behavioural risk factors were mixed. WoW showed promise in the short term by increasing individuals’ uptake of contraception and STI treatment, while condom use and recognition of HIV risk remained unchanged. SRH behaviour change in AGYW is complex, and patriarchal power dynamics frame perceptions, norms and SRH behaviours and influence HIV vulnerability , 36. CT Evidence for the effectiveness of financial incentives to impact health behaviours, such as medication adherence, linkage and retention in care, has so far shown mild, unstained outcomes , 42, 43.CTs with augmented HIV interventions in African AGYW have shown potential to lower HSV‐2, reduce HIV incidence to various degrees, reduce transactional sex and reduce HIV risk behaviours , 50, 51.The appropriate size of the CT is determined by the objectives of the intervention; however, the World Bank has found that CT in ESA needs to provide >20% of household consumption to have a significant impact on health and development . Baird aThis study used self‐reported measures, which may provide unreliable indications of actual behaviours due to recall and social desirability biases. Participants could report different HIV status results at each follow‐up visit potentially biasing the direction of the results. HIV‐positive results were, however, retained for all visits regardless of subsequent responses. Mitigation of the LTFU limitations by linking study records with provincial HIV records was unsuccessful. HIV status reliability in this and future programmes could be strengthened by the inclusion of obligatory HIV/STI testing pre and post intervention to validate self‐reports, though this limits voluntary uptake of testing. The lack of sustained participation in the “care” arm was the greatest confounder and impacted study power and effect sizes. Lack of durability data is a limitation in CT studies, thus, our follow‐up data provide important insights , 55, 56.5A modest CT conditional on attendance of a modular SRH/HIV prevention skills building programme was necessary to incentivize and sustain participation of urban out of school young women in SA. Sustained participation resulted in increased current employment status and moderate improvement of some SRH aspects short term. Uptake and attendance in layered, “young woman centred” developmental programmes to address outcomes of HIV and SRH in young women may be enhanced with modest CT.There are no competing interests.TN conceived of the presented idea with LGB, performed fidelity testing and interviews, and undertook the data management, analysis and wrote the manuscript. FL provided technical guidance and review of the statistical analysis. CP helped develop the skills building manual and program, developed materials and reviewed the manuscript. HE managed the research team and reviewed the manuscript. DR trained facilitators, performed fidelity testing and interviews, and reviewed the manuscript. CW managed the research team and reviewed the manuscript. LL reviewed data analysis and interpretation of the manuscript. LGB conceived of the study design, helped to develop the skills building manual and program and materials, supervised the entire research process, including data analysis and interpretation, and reviewed the manuscript.The Global Fund for HIV, TB and Malaria funded program costs via the Western Cape Department of Health, The Desmond & Leah Tutu Foundation and the Discovery Foundation fund TN's PhD.Nothing to report.Table S1: Intervention optimization defined by RE‐AIM CriteriaClick here for additional data file.Table S2a: Baseline characteristics that are different in WoW completers compared to non‐completersClick here for additional data file.Table S2b: Baseline characteristics that are different in those at follow‐up compared to those not at follow‐upClick here for additional data file.


The neuropathological diagnosis is based on the concurrence of senile plaques (SPs) and neurofibrillary tangles (NFTs) designated as Alzheimer's disease neuropathological changes. However, NFTs develop in the brain decades before the appearance of SPs, and their distribution does not parallel the distribution of SPs. Moreover, NFTs are found in about 85% of individuals at age 65 and around 97% at age 80. SPs occur in 30% at age 65 and 50%–60% at age 80. More than 70 genetic risk factors have been identified in sAD; the encoded proteins modulate cell membranes, synapses, lipid metabolism, and neuroinflammation. Alzheimer's disease (AD) overture provides a new concept and definition of brain aging and sAD for further discussion. AD overture proposes that sAD is: (i) a multifactorial and progressive neurodegenerative biological process, (ii) characterized by the early appearance of 3R + 4Rtau NFTs, (iii) later deposition of β‐amyloid and SPs, (iv) with particular non‐overlapped regional distribution of NFTs and SPs, (v) preceded by or occurring in parallel with molecular changes affecting cell membranes, cytoskeleton, synapses, lipid and protein metabolism, energy metabolism, neuroinflammation, cell cycle, astrocytes, microglia, and blood vessels; (vi) accompanied by progressive neuron loss and brain atrophy, (vii) prevalent in human brain aging, and (viii) manifested as pre‐clinical AD, and progressing not universally to mild cognitive impairment due to AD, and mild, moderate, and severe AD dementia.National Institute on Aging–Alzheimer's Association definition and classification of sporadic Alzheimer's disease (sAD) is based on the assumption that β‐amyloid drives the pathogenesis of sAD, and therefore, β‐amyloid pathology is the  Brain aging with ADNC and sporadic Alzheimer's disease (sAD) form a prevalent continuum unique to humans. Molecular changes affecting cell membranes, cytoskeleton, synapses, lipid and protein metabolism, energy metabolism, neuroinflammation, cell cycle, astrocytes, microglia, and blood vessels precede and occur in parallel with early ADNC; and they are drivers of sAD. Tau pathology is the first neuropathological hallmark but not necessarily the origin of the human brain aging with ADNC, and sAD. However, a significant achievement in understanding AD as a clinically progressive neurodegenerative process was formalized at the beginning of the second decade of this century by the NIA‐AA. Clinically AD was categorized as pre‐clinical AD, MCI due to AD, and mild, moderate, and severe Alzheimer's dementia [Pre‐clinical AD is considered in individuals with measurable brain changes revealed by biomarkers that indicate the earliest signs of AD but have not yet developed symptoms such as memory loss. MCI due to AD is considered in people with biomarker evidence of ADNC plus new but subtle signs such as memory, language, and thinking problems. Pre‐clinical AD is contemplated as a biological situation that makes possible, but not obligatory, the appearance of dementia later in life in the context of ADNC.The selection of biomarkers by the NIA‐AA is in line with the creed of the β‐amyloid cascade hypothesis. Pre‐clinical stage 1 is characterized by primary amyloidosis and assessed by the positivity of β‐amyloid biomarkers and negativity of tau biomarkers. Stage 2 is asymptomatic cerebral amyloidosis plus “downstream” neurodegeneration based on high CSF tau/P‐tau ratio, neuronal dysfunction, cortical thinning, and hippocampal atrophy. Pre‐clinical stage 3 is distinguished by cerebral amyloidosis, neurodegeneration, and subtle cognitive decline.The early presence of positive tau‐PET in the inner regions of the temporal cortex in the absence of positive β‐amyloid markers does not merit the categorization of pre‐clinical AD according to the current definition of the NIA‐AA.However, cognitive status correlates with NFT burden rather than β‐amyloid plaques .5The term “primary age‐related tauopathy” (PART) was coined to include cases with NFT pathology at stages I–IV of Braak in the absence of β‐amyloid plaques . PatientAPOEε4, rs28834970 PTK2B, rs6733839 in the BIN1, and CR1 genes, and a higher prevalence of APOEε2 [the MAPT H1 haplotype [Genetic studies carried out in neuropathologically‐verified PART cases have shown a lower prevalence of f APOEε2 , 114. Inaplotype . The proaplotype , 117.6Molecular changes in brain aging and sAD are not restricted to β‐amyloid and abnormal tau accumulation. Multiple systems are primarily dysfunctional or secondarily damaged by abnormal β‐amyloid and tau species. Added molecular changes compromise: (i) synapses; neurotransmitters, neuromodulators, and related receptors, including acetylcholine and acetylcholine receptors, glutamate and glutamate receptors, γ‐aminobutyric acid (GABA) and GABA receptors, serotonin and 5‐hydroxytryptamine (5‐HT) receptors, noradrenergic system, adenosine receptors, endocannabinoids, cannabinoid receptors, endorphins, and orexin; (ii) trophic factors and receptors; (iii) mitochondria and oxidative phosphorylation; (iv) oxidative and nitrosative stress damage to lipids, nucleic acids, and proteins; (v) mitochondria/endoplasmic reticulum interactions; (vi) endoplasmic reticulum stress; (vii) failure of the ubiquitin‐proteasome system and autophagy to remove debris; (viii) granulovacuolar degeneration; (ix) purine metabolism; (x) histone modifications, DNA methylation, and hydroxymethylation; (xi) non‐coding RNAs; (xii) protein synthesis; (xiii) altered cell cycle and re‐entry; and (xiv) cell death. Other key elements in the pathogenesis of brain aging and sAD are early dysfunctional astrocytes and microglia, followed by altered oligodendrocytes; and alterations in the neurovascular system manifested as early reduction of the cerebral blood flow and abnormal blood barrier function. All these factors, together with β‐amyloid and tau, contribute to neuronal cell death and reduced neuronal connectivity , 120.Notably, several of those determining molecular changes linked to brain aging and sAD precede the appearance of NFTs and SPs, as demonstrated by their occurrence in brain regions not affected by SPs and NFTs at NFT stages I and II. Molecular changes progress with particular profile‐, time‐, and region‐dependent patterns . MoleculNFTs and β‐amyloid, in turn, potentiate all the above‐mentioned molecular alterations, thereby creating positive feedback for the degenerative process . Other pTable 7The natural history of ADNC changes during the human lifespan shows the early formation of NFTs, followed by the appearance of β‐amyloid deposits decades later , 61, 69.Another proposal suggests the existence in the human brain of a PART to which β‐amyloid deposition is added in a time‐, rate‐ and region‐dependent manner in the different AD categories, reliant on genetic factors involved in the production of β‐amyloid .Not surprisingly, the mutually exclusive hypotheses formulated to explain sAD are not satisfactory and have not produced significant beneficial results when applied in clinical trials. In short, anti‐β‐amyloid therapies have been unsuccessful not because they cannot reduce β‐amyloid deposits, as they indeed do, but rather because they do not stop the progression of the disease. In addition, therapies geared to reducing abnormal tau deposits face difficulty picking up the critical tau species, which may block NFT formation. Moreover, current therapies do not contemplate actions directed to the multiple genetic and molecular factors, which are indeed the inducers of ADNC.A new concept and definition of brain aging and sAD are brought forward for further discussion. AD overture guidelines advance that sAD is: (i) a multifactorial and progressive neurodegenerative biological process, (ii) characterized by the early appearance of 3R + 4Rtau NFTs, (iii) later deposition of β‐amyloid and SPs, (iv) with particular non‐overlapped regional distribution of NFTs and SPs, (v) which are preceded by, and occurring in parallel with, molecular changes involving determining sub‐cellular structures and functions; (vi) accompanied by progressive neuron loss and brain atrophy, (vii) prevalent in human brain aging, and (viii) manifested as pre‐clinical AD, and progressing not universally to mild cognitive impairment due to AD (MCI‐AD), and mild, moderate, and severe AD dementia (ADD).The neuropathological characteristics and clinical correlates of sAD overture compared with NIA‐AA guidelines are summarized in Figure The “ABC” score for ADNC proposed by the NIA‐AA is helpful, but Braak β‐amyloid scores are similar to CERAD neuritic plaque scores and might also be used to categorize the extension of plaques in the cerebral cortex. As a supplementary note, immunohistochemistry with validated antibodies against P‐tau and β‐amyloid is mandatory. The critical point that distinguishes the AD overture definition from the NIA‐AA proposal is the early appearance of tau pathology as the first neuropathological ADNC marker of sAD. The β‐amyloid cascade hypothesis is no longer considered the cause of sAD. However, the early appearance of tau pathology does not presuppose that tau pathology is the sAD's origin. As indicated in Figure Regarding the value of biomarkers suggested by the NIA‐AA, AD overture shifts to recognizing early tau pathology, mainly revealed by tau‐PET, as the earliest marker of sAD. However, new indicators are needed to detect early molecular alterations preceding, or occurring in parallel with, tau and β‐amyloid pathology. Among them, changes in protein and lipid composition of cell membranes, and altered membrane signaling with the cytoskeleton, mitochondria, and vesicles are significant targets for further research. Age‐related astroglial and microglial alterations, modification of neuroinflammatory profiles, and cerebral blood vessel dysfunction with age are determining, as well.Finally, the clinical classification of AD overture also differs from the NIA‐AA classification in categorizing pre‐clinical sAD. Nevertheless, the terms MCI due to AD and mild, moderate, and severe Alzheimer's dementia are modified slightly in the new classification. MCI due to AD is named MCI‐AD, and mild, moderate, and severe Alzheimer's dementia, are named mild, moderate, and severe ADD. ADD is introduced to avoid confusion between AD (Alzheimer's disease) and AD dementia (restricted to the most advanced AD phase).Regarding pre‐clinical sAD, AD overture guidelines propose that stage 1 corresponds to asymptomatic primary tauopathy as revealed with high‐resolution tau‐PET. Stages 2–4 are similar to stages 1–3, respectively, proposed by the NIA‐AA , but tauThe concept of human brain aging and sAD proposed in AD overture seems more closely adapted to the natural history of events during brain aging and sAD. AD overture has additional clinical implications. The diagnosis of pre‐clinical sAD has been advanced for several decades. Moreover, learning about molecular changes involving various structures and signaling pathways preceding or occurring in parallel with the appearance of tau pathology and β‐amyloid deposition may be an opportunity to design new unconventional, breakthrough therapies.APP, PSEN1, and PSEN2.AD overture guidelines are centered on human brain aging and sAD. At present, we do not have enough information to apply the same parameters, particularly those linked to molecular brain changes at pre‐clinical stages and pre‐clinical biomarkers, to fAD caused by mutations in IF has written the paper.The project leading to these results received funding from the “la Caixa” Foundation under the agreement LCF/PR/HR19/52160007: HR18‐00452. I thank CIBERNED, Instituto de Salud Carlos III, and the CERCA programme of the Generalitat de Catalunya for institutional support.The authors declare no potential conflict of interest.


To improve the diagnosis and survival of children living with HIV (CLWH), the World Health Organization recommends testing approaches beyond traditional infant HIV testing programmes. Information about undiagnosed HIV prevalence among children of varying ages in the general population is needed to guide innovative national/subnational case‐finding and testing approaches.We used the Cost‐Effectiveness of Preventing AIDS Complications (CEPAC)‐Pediatric model to estimate the prevalence of undiagnosed HIV in 2‐, 5‐ and 10‐year‐old children in South Africa, Côte d'Ivoire and Zimbabwe in 2018. We simulated cohorts of children born in 2008 (10‐year‐olds), 2013 (5‐year‐olds) and 2016 (2‐year‐olds). Country‐/year‐specific inputs for pregnant/breastfeeding women included: HIV prevalence (4.2–32.3%), HIV incidence (0.03–0.24%/month), knowledge of HIV status (27–89%) and antiretroviral drug coverage (36–95%). Paediatric inputs included early infant testing coverage (6–95%) and breastfeeding duration (0–20 months). We projected the proportion of surviving CLWH in whom HIV remained undiagnosed and the undiagnosed HIV prevalence among surviving children of each age in the general population. For children born in 2016, we projected survival and diagnosis of all CLWH through 2026. We conducted sensitivity analyses on model parameters.In 2018, the projected proportion of surviving CLWH whose HIV remained undiagnosed in South Africa/Côte d'Ivoire/Zimbabwe was 44.2%/55.8%/52.9% among 2‐year‐old CLWH; 29.0%/37.8%/33.2% among 5‐year‐old CLWH; and 18.3%/25.4%/23.1% among 10‐year‐old CLWH. Projected general population undiagnosed HIV prevalence in South Africa/Côte d'Ivoire/Zimbabwe was 0.44%/0.32%/0.68% among 2‐year‐olds; 0.25%/0.17%/0.41% among 5‐year‐olds; and 0.24%/0.14%/0.38% among 10‐year‐olds. Among all CLWH born in 2016, 50–54% were projected to die without HIV diagnosis (and subsequently without treatment) within 10 years after birth; 80–85% of these deaths occurred in the first 2 years.Projected population‐level undiagnosed HIV prevalence is low and sharply decreases after age 2, with more CLWH dying than being diagnosed. Despite low undiagnosed prevalence in the general population of older children, we project that a large proportion of CLWH remain undiagnosed, suggesting that innovative strategies targeting untested children of all ages outside of health facility settings should be prioritized. Programmes could consider routine testing of the general population of children below 2 in all settings and children of all ages in high‐prevalence settings. Following the scale‐up of HIV testing and universal antiretroviral therapy (ART) for pregnant/breastfeeding women, from 2010 to 2021, estimated numbers of new children living with HIV (CLWH) globally dropped from 320,000  to 160,000  . Fo. Fo14]. 2.4We projected early (intrauterine/intrapartum) vertical transmission, total (intrauterine/intrapartum/postpartum) vertical transmission by end of breastfeeding and survival among 2008, 2013 and 2016 birth cohorts in each country. For each calendar‐year birth cohort, we reported (1) the proportion of surviving CLWH with undiagnosed HIV, and (2) the proportion of children surviving to 2018 with undiagnosed HIV among the general population . We also projected the absolute number of undiagnosed CLWH of each age in South Africa . To dete2.5Model input parameters and vertical transmission risks across plausible ranges , Côte d'Ivoire (0.14–0.32%) and Zimbabwe 0.38–0.68%), with a steeper decline in undiagnosed prevalence between ages 2 and 5 than between ages 5 and 10. However, many CLWH surviving to age 2 remain undiagnosed: 44% in South Africa, 56% in Côte d'Ivoire and 53% in Zimbabwe. Moreover, more than 50% of all CLWH in modelled countries are projected to die by age 10 without ever having their HIV diagnosed and subsequently treated, with most deaths occurring within the first 2 years of life. Results are consistent with data from the Zimbabwe Population‐based HIV Impact Assessment, which reports that among CLWH aged 1–4, 5–9 and 10–14 years, 47%, 36% and 23% have undiagnosed HIV, respectively [–0.68%, wWe find that while the HIV care continuum for women and children has improved dramatically over time, there is room for improvement in identifying CLWH, particularly in the first 2 years of life. In all settings, countries should scale up paediatric HIV testing at higher‐yield sites or deploy targeted strategies, such as index testing. We project that even when only 24% of the total population of pregnant/breastfeeding women with HIV go untreated, these women contribute 80% of total vertical transmission, consistent with prior findings . This hiIn some settings, routine screening of the general population of children could be cost‐effective, especially at younger ages. A recent analysis found that PITC would be cost‐effective in South Africa if the undiagnosed prevalence is at least 0.2–0.3%; our analysis projects that undiagnosed prevalence in South Africa in 2018 is 0.24–0.44%, depending on age . While aOur sensitivity analysis results can inform which settings should be prioritized for HIV testing of pregnant/breastfeeding women and children. For example, because lower knowledge of HIV status in pregnant/breastfeeding women is associated with higher paediatric undiagnosed HIV prevalence, subnational locations with limited access to or engagement in antenatal/postnatal care could implement PITC in settings, such as well‐child visits or community‐wide outreach programmes. HIV diagnosis during late pregnancy and breastfeeding is also critical; the optimal location, timing and frequency of repeated HIV screening among pregnant/breastfeeding women is an area of active investigation , 42. ImpOur study has several limitations. First, there are limited data against which we can validate total vertical transmission. One strength of our model‐based analysis is that it can simulate outcomes, including total vertical HIV transmission, for women and children missed by traditional testing programmes. This differentiates our analysis from clinical trials and data collection conducted primarily in antenatal care or infant testing clinics, but long‐term model‐based estimates are inherently uncertain. Notably, likely due to our estimates about low re‐testing rates in pregnancy/breastfeeding, CEPAC‐P estimates of yearly vertical transmission are generally higher than UNAIDS estimates. Second, our estimate of the proportion of women with known HIV status assumes that available data encompass all testing done during pregnancy/breastfeeding; if additional testing is done at delivery or during breastfeeding, undiagnosed prevalence will likely be lower , 28, 29.5In this simulation model‐based analysis, we projected that undiagnosed HIV prevalence among 2‐, 5‐ and 10‐year‐old children in the general population in South Africa, Côte d'Ivoire and Zimbabwe is low, and if ART and HIV care continuum parameters in pregnancy/breastfeeding improve over time, the undiagnosed prevalence may continue to decrease. We project that undiagnosed prevalence declines more steeply between ages 2 and 5 than between ages 5 and 10, and that more than half of CLWH die before HIV is diagnosed, with most of these deaths occurring in the first 2 years of life. We conclude that in addition to strengthening traditional infant HIV testing, programmes should: (1) prioritize deploying and maximizing coverage of innovative targeted testing in all settings, including testing of sick children/children exhibiting OI symptoms , and index testing or screen‐and‐test , and (2) depending on feasibility, consider implementing routine testing of the general population of children below 2 in all settings and children of all ages in high‐prevalence settings .The authors have no competing interests to disclose.All authors have made substantial contributions to the conception and design, acquisition of data, and/or analysis and interpretation of the data. The authors have participated in drafting or critically revising this article. The authors have given final approval of the submitted version.This work was supported by the World Health Organization, with additional support for model development from the US National Institutes of Health and R01HD079214 (Ciaranello), K08HD094638 (Neilan), K08HD101342  and U01AI069924 (Davies and Johnson).Supporting informationThe Supplemental Technical Appendix provides additional details about the CEPAC‐P model structure and analysis‐specific supporting information.Click here for additional data file.


Shared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen.N = 45,749; 2010‐09 to 2019‐05), respiratory syncytial virus , or severe acute respiratory syndrome coronavirus 2  using population‐based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality.We conducted a retrospective cohort study to identify predictors of 30‐day all‐cause mortality following hospitalization with influenza , 697 (2.9%), and 1880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS‐CoV‐2, respectively. Shared predictors of increased mortality included older age, male sex, residence in a long‐term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS‐CoV‐2. Few comorbidities were associated with mortality among patients with SARS‐CoV‐2 as compared with those with influenza or RSV.Our findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors. At the same time, laboratory diagnostic testing is transitioning to pre‐pandemic approaches, where only a subset of hospitalized patients with viral respiratory or influenza‐like illness receive laboratory‐confirmed diagnoses.We conducted an observational study using extensive health administrative data from Ontario, Canada, to identify the direction and magnitude of shared and divergent predictors of 30‐day all‐cause mortality following hospitalization with influenza, RSV, or SARS‐CoV‐2 (prior to vaccine availability or variant emergence).22.1We conducted a retrospective cohort study of patients hospitalized with influenza, RSV, or SARS‐CoV‐2 using population‐based laboratory and health administrative data from Ontario, Canada (population 14.7 million).2.22.2.1We generated three study cohorts to assess predictors of severe outcomes among patients hospitalized with influenza, RSV, and SARS‐CoV‐2, respectively. Patients with influenza and RSV were identified using hospitalization data from the Canadian Institute for Health Information's Discharge Abstract Database (DAD) during the 2010–2011 to 2018–2019 respiratory virus seasons. DAD captures administrative, clinical, and demographic information on all hospital discharges in Canada. Patients were considered hospitalized with influenza if their discharge abstract contained any of the following ICD‐10 codes: J09, J10.0, J10.1, J10.8, J11.0, J11.1, or J11.8. Patients were considered hospitalized with RSV if their discharge abstract contained any of the following ICD‐10 codes: J12.1, J20.5, J21.0, or B97.4. Case definitions were validated in Ontario against laboratory confirmation and showed high specificity  and positive predictive values .We used DAD, the Ontario Laboratories Information System (OLIS), and the Public Health Case and Contact Management System (CCM) to identify patients hospitalized with SARS‐CoV‐2 between March 1 and December 1, 2020. OLIS is an electronic repository of Ontario's laboratory test results, containing information on laboratory orders, patient demographics, provider information, and test results. CCM is a central data repository for all COVID‐19 case management, contact management, and reporting in Ontario. Patients were considered hospitalized with SARS‐CoV‐2 if: (1) they were documented as hospitalized in DAD and had a positive polymerase chain reaction test for SARS‐CoV‐2 within 14 days before or 3 days after hospital admission; or (2) they were documented as hospitalized in CCM.2.2.2Our primary outcome of interest was 30‐day all‐cause mortality following hospital admission with influenza, RSV, or SARS‐CoV‐2. We used the Registered Persons Database (RPDB) and CCM to identify patients who died within 30 days of hospital admission. RPDB contains basic demographic information including age, sex, postal code, and date of death among all residents with an Ontario health card.2.3Hospitalized patients were excluded if: they were not eligible for the Ontario Health Insurance Plan; their birthdate, sex, or postal code was missing from RPDB; their residential postal code was outside of Ontario; they were older than 105 years according to their birthdate in RPDB; or their recorded death date predated hospital admission , hypertension, cardiac ischemic disease, congestive heart failure, stroke, dementia or frailty, chronic kidney disease, advanced liver disease, and immunosuppression .2.4.3Other predictors of severe outcomes included residence in a long‐term care home (LTCH),2.5Data processing and analyses were conducted using SAS version 9.4 . Frequencies and proportions were used to describe the distribution of risk factors among individuals hospitalized with influenza, RSV, or SARS‐CoV‐2. Modified Poisson regression  was used to assess the association between predictors and 30‐day all‐cause mortality. Modified Poisson regression was used over logistic regression to estimate risk ratios and avoid misinterpretation of odds ratios obtained from logistic regression.33.1We observed 45,749 influenza hospitalizations, 24,345 RSV hospitalizations, and 8988 SARS‐CoV‐2 hospitalizations after applying inclusion and exclusion criteria Figure . Patient3.2Patients hospitalized with SARS‐CoV‐2 had the highest crude 30‐day all‐cause mortality rate .In unadjusted models, shared predictors of mortality included: older age, residence in a LTCH, immunization against seasonal influenza, COPD, cardiac ischemic disease, congestive heart failure, hypertension, diabetes, dementia/frailty, stroke, and chronic kidney disease Figure . Larger In adjusted models, shared predictors of mortality included: older age, male sex, residence in a LTCH, and chronic kidney disease Figure . Similar3.3Rural residence was associated with increased 30‐day all‐cause mortality among patients hospitalized with RSV  and SARS‐CoV‐2 , but not among patients hospitalized with influenza . Immunization against seasonal influenza was associated with decreased 30‐day all‐cause mortality among patients hospitalized with influenza  but not patients hospitalized with RSV  or SARS‐CoV‐2 . Finally, cardiac ischemic disease, congestive heart failure, dementia/frailty, and immunosuppression were associated with increased all‐cause mortality among patients hospitalized with influenza and RSV after adjustment for all other predictors, but not among patients hospitalized with SARS‐CoV‐2.4We identified shared and divergent predictors of mortality among patients hospitalized with influenza, RSV, or SARS‐CoV‐2 using population‐based health administrative data from Ontario, Canada. In multivariable models, common predictors of 30‐day all‐cause mortality following hospitalization included older age, male sex, residence in a LTCH, and chronic kidney disease.Older age and male sex were predictive of increased mortality across all respiratory virus cohorts, which aligns with numerous studies from high‐income countriesResidence in a LTCH was also a common predictor of 30‐day all‐cause mortality; however, associations were weaker among patients hospitalized with SARS‐CoV‐2. Differences in magnitudes of association may be due to greater selection bias of LTCH residents hospitalized with SARS‐CoV‐2 in comparison to those with influenza or RSV. For example, in Ontario, less than one quarter of COVID‐19‐positive LTCH residents were hospitalized prior to death, compared with nearly 80% of COVID‐19‐positive community residents during the first wave of the pandemic.Similar to previous studies,We did not observe associations between area‐level social determinants of health and 30‐day all‐cause mortality following hospitalization with all three viruses, despite their associations with infection transmission risk.This study is limited by potential misclassification of influenza and RSV cases, as we identified patients using their hospitalization discharge codes rather than diagnostic test results. However, case definitions were validated against a population of hospitalized patients who received diagnostic testing for influenza or RSV in the Ontario population.with the virus). The additional public health dataset available for SARS‐CoV‐2  allowed us to compare death outcomes of hospitalized patients with SARS‐CoV‐2  to their mortality within 30 days of hospitalization in health administrative data. Thirty‐day all‐cause mortality had 97% positive predictive value against death due to COVID‐19 in CCM. Thus, we expect 3% of outcomes to potentially reflect deaths with SARS‐CoV‐2. In the absence of approaches to adequately address this misclassification for all viruses, we acknowledge the small bias as an important limitation.Moreover, the study outcome as defined may capture deaths attributable to the virus or deaths in the context of an incidental infection , and prioritize prevention and therapeutic strategies during rapid emergence of respiratory viruses.The authors declare no competing interests that are relevant to the content of this article.Mackenzie A. Hamilton: Conceptualization; formal analysis; investigation; methodology; visualization; original draft preparation. Ying Liu: Data curation. Andrew Calzavara: Data curation; methodology. Maria E. Sundaram: Conceptualization; formal analysis; investigation; methodology. Mohamed Djebli: Conceptualization; formal analysis; investigation; methodology. Dariya Darvin: Visualization. Stefan Baral: Supervision. Rafal Kustra: Formal analysis; methodology; supervision. Jeff C. Kwong: Conceptualization; funding acquisition; methodology; project administration; supervision. Sharmistha Mishra: Conceptualization; funding acquisition; methodology; project administration; supervision.https://publons.com/publon/10.1111/irv.13004.The peer review history for this article is available at Suppplementary Text. Derivation of neighbourhood‐level social determinants of health.Table S1. Definitions of underlying medical conditions among hospitalized patients.Table S2. Databases and claim codes to identify patients immunized against seasonal influenza.Table S3. Unadjusted predictors of 30‐day all‐cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS‐CoV‐2 (2020‐03 to 2020‐12).Table S4. Adjusted predictors of 30‐day all‐cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS‐CoV‐2 (2020‐03 to 2020‐12).Click here for additional data file.


Immunotherapy‐antiangiogenesis combination therapy has achieved excellent survival outcomes in hepatocellular carcinoma (HCC) in clinical trials. However, the combination therapy for HCC outside clinical trials is not well studied, and predictive factors are lacking. Here, we retrospectively analyzed the efficacy and safety of immunotherapy‐antiangiogenesis combination therapy in unresectable HCC patients in a real‐world setting.(PD‐1) inhibitor and antiangiogenic agent between April 2018 and July 2021 in China.We conducted a four‐center, retrospective study of unresectable HCC patients who received the combination of programmed death 1 In total, 136 patients were enrolled in the cohort. The objective response rate (ORR) and disease control rate (DCR) were 38.0% and 81.8%, respectively. The median time to progression (TTP), progression‐free survival (PFS), and overall survival (OS) were 7.2, 7.3, and 19.6 months, respectively. The multivariate analysis indicated that ECOG performance status score (PS) 2 was a significantly independent negative factor of ORR. Moreover, ECOG PS 2, peritoneum metastasis and previous immunotherapy were found to be independent negative predictors of PFS. A shorter OS was associated with ECOG PS 2, peritoneum metastasis, the presence of previous immunotherapy, Child‐Pugh stage B, and high alpha‐fetoprotein (AFP) concentration. One hundred and twenty‐five patients (91.9%) reported adverse events (AEs) with any grade.We elucidated the efficacy and safety of immunotherapy‐antiangiogenesis combination therapy and identified potential predictors for response and survival in a real‐world cohort of patients with unresectable HCC. Immunotherapy‐antiangiogenesis is an efficacious strategy for unresectable HCC. We identified potential predictors for response and prognosis in HCC. Patients were excluded if they presented (1) combined therapy for only one cycle; (2) no available follow‐up data; (3) no available data for baseline assessment and response assessment; (4) a second primary tumor in the recent 5 years; (5) pathologic finding was hepatocellular carcinoma with sarcoma or hepatic neuroendocrine carcinoma.In total, data of 81 patients were excluded, the remaining 136 patients met the enrollment criteria and were enrolled for analysis. All data, including treatment strategy, laboratory results, and radiological assessments were collected from patients' electronic medical records. The study was performed in accordance with the Declaration of Helsinki and was approved by the Medical Ethics Committee of the four participating hospitals.2.2The combination strategy was determined based on previous treatment strategy, individual characteristics, patient willings, and economic consideration. Six available PD‐1 inhibitors were sintilimab, toripalimab, camrelizumab, pembrolizumab, nivolumab, and tislelizumab, which were administrated intravenously according to the following doses: sintilimab 200 mg, toripalimab 240 mg, pembrolizumab 200 mg, or tislelizumab 200 mg every 3 weeks, camrelizumab 200 mg, or nivolumab 3 mg/kg every 2 weeks. Simultaneously, patient received antiangiogenic therapy, including lenvatinib, sorafenib, regorafenib, apatinib, or bevacizumab, which was administered orally except bevacizumab. Lenvatinib was given 8 mg/day (body weight <60 kg) or 12 mg/day (body weight ≥60 kg). The initial dose of sorafenib was 400 mg/day and increased to 800 mg/day if tolerated. Regorafenib was given 80 mg/day from week 1 to 3 of every 4‐week cycle. Patients received apatinib at a dose of 250 mg daily or bevacizumab 7.5 mg/kg every 3 weeks intravenously.According to tumor burdens and goal of treatment, selected patients received concomitant LRT for at least one‐time within 1 month before or after the combined systemic therapy, which including TACE, ablation, radiation and/or seed implantation. Patients who experienced serious treatment‐related adverse events (TRAEs) would have dose delay, dose reduction, treatment interruption, or discontinuation based on the grade of toxicity. Patients with active hepatitis B virus (HBV) infection received antiviral treatment synchronously.2.3Radiological data were collected based on dynamic computed tomography (CT) and/or magnetic resonance imaging (MRI) at baseline and every 8–12 weeks thereafter. Tumor responses were evaluated according to mRECIST:ORR was determined as the sum of CR and PR. Disease control rate (DCR) was defined as the percentages of CR, PR, and SD. PFS referred to the time interval from treatment initiation to progression or death from any cause. Time to tumor progression (TTP) was determined as the time from the initial dose to progression confirmed by radiology. Overall survival (OS) was calculated from the start of the combination treatment until death. TRAEs were adverse events (AEs) that associated with PD‐1 inhibitor and antiangiogenic agent rather than LRT, which were collected according to the Common Terminology Criteria for Adverse Events, v 5.0.2.42 test or Fisher's exact test. The PFS and OS were estimated by Kaplan–Meier method, univariate analysis was preformed using Logrank test, all covariates with p < 0.05 in univariate analyses were then performed in a multivariate analysis using Cox proportional hazards regression model. The hazard ratio (HR) and confidence interval (CI) were calculated. Two‐sides p value <0.05 was considered statistically significance. Statistical analyses were conducted using IBM SPSS version 23 and GraphPad Prism version 8.00.Categorical variables in clinical characteristics were statistically analyzed by Pearson's X33.1One hundred and thirty‐six unresectable, locally advanced or metastatic HCC patients who have received PD‐1 inhibitor plus antiangiogenic agent with or without additional LRTs were included in the retrospective cohort study Figure , with thn = 115, 84.6%) with the median age of 58 (range 14–84 years), 78 patients (57.4%) had an Eastern Cooperative Oncology Group performance status score (ECOG PS) of 0 or 1, 54 patients (39.7%) had a history of alcohol use. The majority of patients were positive for HBV infection (91.2%), and had liver cirrhosis (79.4%) with an AFP concentration below 400 IU/ml (53.7%). A total of 80.1% of patients were Child‐Pugh stage A and 91.2% of patients had Barcelona Clinic Liver Cancer (BCLC) stage C disease. One hundred and one patients (74.3%) had extrahepatic disease, lymph node (44.9%) was the most frequent site for metastasis, followed by lung (38.2%), peritoneum (8.8%), bone (8.1%), adrenal gland (5.1%), and intra‐abdominal implantation (5.1%). Additionally, half of patients (50.0%) had macrovascular invasion. Prior therapies were diverse, 67 (49.3%), 92 (67.6%), 14 (10.3%), and 47 (34.6%) patients received prior surgery, LRT, immunotherapy, and antiangiogenic therapy, respectively, and 56 patients (41.2%) received previous systemic treatment as first‐line or subsequent‐line therapy.The baseline patient characteristics are listed in Table In the cohort, patients were given different combination strategy of PD‐1 inhibitors plus antiangiogenic agents Table . The mos3.2Among 136 patients, 15 cases were not available for best response assessment, five patients died before the first image evaluation, 10 patients lost follow‐up image data, and remaining 121 patients had at least one available image for tumor response assessment. Complete radiographic response occurred in three (2.5%) locally advanced HCC patients with or without portal vein tumor thrombus. Two of them treated with additional TACE reached CR in 1.3 to 4.4 months, another without LRT had CR in 8.9 months. Forty‐three patients achieved PR, resulting in an ORR of 38.0%. Fifty‐three participants (43.8%) had SD and 22 participants (18.2%) had PD. The DCR was 81.8%. The best reduction from baseline in tumor measurement is shown in Figure p < 0.001) , patients with peritoneum metastasis had a shorter PFS than those without peritoneum metastasis . Moreover, patients who received prior immunotherapy had a shorter PFS than those who did not receive prior immunotherapy .In the cohort, 121 cases were available for best response assessment, median time to progression (TTP) was 7.2  months Figure , median 3.4p = 0.005), the present of peritoneum metastasis , previous immunotherapy , Child‐Pugh stage B , and high AFP concentration  were independent predictors for OS  months Figure , 1‐year 3.5Six available PD‐1 inhibitors and five antiangiogenic agents were applied in our study, the combination treatment strategy was individualized therapy. Considering the high cost of bevacizumab and the clinical practice in the real world,p = 0.31), and median PFS  in LRTs group were comparable to those in non‐LRTs group, while patients in LRTs group had a longer OS than those in non‐LRTs group , but had no significant differences  patients received additional LRTs combined with systemic therapy Table , the ORRes Table .3.6One hundred and twenty‐five patients (91.9%) experienced at least one TRAE Table . Most co4Combination therapy by synergistic antitumor effects is suggested as an efficacious strategy for many cancers. The strategy using PD‐1/PD‐L1 inhibitor combined with antiangiogenic therapy has been successfully applied in HCC.The novel patterns of response for anti‐PD‐1/PD‐L1 antibody therapy are pseudoprogression (PSPD) and hyperprogressive disease (HPD).Currently, different combination patterns of PD‐1/PD‐L1 inhibitor plus antiangiogenic agent are under investigation in clinical trials.LRTs are commonly used in HCC and have been proved to increase antitumor immune response by exposing neo‐tumor‐associated antigens via tumor necrosis.At present, predictors that enrich for a population more likely to benefit from PD‐1 inhibitor combined with antiangiogenic agent have not been validated in HCC. Our study demonstrated ECOG PS was independent predictor for response and prognosis, while factors as peritoneum metastasis, the presence of previous immunotherapy, Child‐Pugh stage B and high AFP concentration were negative predictors for prognosis in HCC. Clinical trial data and meta‐analyzed real‐world data suggested patients with impaired ECOG PS achieved a lower response rate when treated with PD‐1 inhibitor when compared with good ECOG PS population in a wide range of tumors such as non‐small cell lung cancer, advanced melanoma, and urologic cancer.The spectrums of TRAEs in our series were consistent with the known AEs of each drug. Grade ≥3 TRAEs to the combination of PD‐1/PD‐L1 inhibitor and antiangiogenic agent occurred from 29% to 93% in clinical trials,Our study has some limitations. First, it is a retrospective study and the sample size was relatively small, which might reduce the statistic power. Second, the regimens of PD‐1 inhibitors and antiangiogenic agents were heterogeneous and some were off‐label used in the study, though we have analyzed whether the combination strategy would affect the response or prognosis, independent prospective study with fixed regimens need to apply in future. Third, most patients (91.2%) had an etiology of HBV infection rather than other etiological factors in the cohort, thus the results may not be applied for HCC with other etiologies. Finally, biomarkers such as the expression level of PD‐L1 and tumor mutation burden are potential indexes for selecting patients who would benefit from immunotherapy across many cancers, but these biomarkers were not recorded and analyzed in our series.5In summary, we elucidated the efficacy and safety of the combination of PD‐1 inhibitor and antiangiogenic therapy in a real‐world cohort of patients with unresectable HCC, and we identified potential predictors for response and prognosis in HCC, aiming at selecting patients mostly likely to benefit from the combination therapy. Further prospective studies with large‐scale samples, fixed combination strategy, and biomarker detections are needed.The authors declared no potential conflict of interest.Junlin Yao: Conceptualization, data collection, data analysis, and article writing. Xudong Zhu: Data collection, data analysis, and article writing. Zhiheng Wu: Data collection, data analysis, and article writing. Qing Wei: Data collection and review of the manuscript. Yibo Cai: Data collection and review of the manuscript. Yu Zheng: Conceptualization and review of the manuscript. Xinyu Hu: Data collection and review of the manuscript. Hong Hu: Conceptualization and review of the manuscript. Xiangyu Zhang: Review of the manuscript. Hongming Pan: Conceptualization and review of the manuscript. Xian Zhong: Conceptualization, data collection, and writing–review and editing. Weidong Han: Conceptualization, supervision, and writing–review and editing.The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, China (no. 20210405–36).Figure S1Click here for additional data file.Table S1Click here for additional data file.


The Pfizer‐BioNTech coronavirus disease 2019 (COVID‐19) vaccine is extensively used worldwide, and its safety has been proven. Herein, we report a case of an acute necrotic disorder in the small intestine post‐COVID‐19 vaccination. The patient developed severe abdominal pain the day after the first vaccination. Contrast‐enhanced computed tomography showed extensive ileum wall thickening and ascites. Colonoscopy revealed a ring‐shaped ulcer and stricture in the terminal ileum. Ileocecal resection was performed, and the patient did not have further episodes of a necrotic disorder in the small intestine. Although it is unknown if this event is associated with vaccination, and this occurrence also does not outweigh the efficacy and safety of the Pfizer‐BioNTech COVID‐19 vaccine, gastroenterologists need to be aware of this rare case, given its noteworthy timing. The coronavirus disease‐2019 (COVID‐19) emerged in China in 2019 and rapidly spread worldwide. It was caused by the severe acute respiratory syndrome coronavirus 2 and resulted in multiple severe cases and deaths.A 72‐year‐old male visited the emergency department complaining of acute‐onset abdominal pain. He had received his first dose of the Pfizer‐BioNTech BNT16B2b2 mRNA vaccine one day before visiting the hospital. He had a history of cerebral infarction and immunoglobulin G (IgG) 4‐related kidney disease. His current medications were clopidogrel (75 mg) and prednisolone (5 mg). He was conscious and afebrile. Physical examination revealed abdominal tenderness without rebound tenderness or guarding. He had decreased bowel sounds and normal vital signs. Laboratory testing revealed a slightly elevated white blood cell count of 14,400/μl . Other markers, including D‐dimer, were normal. He was admitted to the hospital for suspected enteritis.One day after his admission, the abdominal pain worsened. His white blood cell count was elevated to 17,100/μl, C‐reactive protein level was 13.70 mg/dl , and D‐dimer level was 4.6 μg/ml . Contrast‐enhanced computed tomography showed extensive ileum wall thickening and ascites; there were no abnormal findings in the vessels around the terminal ileum Figure . A colonFigure . The finAmong patients with COVID‐19, both arterial and venous thrombosis are reportedly noted in those with a strong thrombotic tendency. Specifically, cerebral infarction, myocardial infarction, and limb artery thrombosis have been reported as arterial thrombosis events, while deep vein thrombosis and pulmonary thromboembolism have been reported as venous thrombosis events.Three vaccines have been approved in Japan: two mRNA vaccines, developed by Pfizer/BioNTech and Moderna, and the virus vector vaccine, developed by AstraZeneca. These vaccines do not contain a live virus. Although genetic information is inoculated into the body, it does not alter human genetic information. In addition, the mRNA is broken down within a few days after vaccination, and the spike protein produced disappears within two weeks after vaccination. Based on the mechanism of the mRNA vaccine, few adverse reactions are expected.Mild, local, and systemic reactions have been reported in patients recently vaccinated against COVID‐19. According to Chapin‐Bardales et al., the most frequently reported local and systemic reactions after the first COVID‐19 vaccine dose were injection site pain (67.8%), fatigue (30.9%), headache (25.9%), and myalgia (19.4%). Reactogenicity was substantially greater after the second dose for both vaccines, particularly for systemic reactions, including fatigue (53.9%), headache (46.7%), myalgia (44.0%), chills (31.3%), fever (29.5%), and joint pain (25.6%).The authors declare that they have no conflict of interest.None.Not applicable.


Body mass index is associated with carotid intima‐media thickness and distensibility in adults and children.To examine whether general and specific fat depots are associated with these markers of arterial health at school age.This cross‐sectional analysis was embedded in a population‐based prospective cohort study among 4708 children aged 10 years. Body, lean and fat mass index were estimated by dual‐energy X‐ray absorptiometry. Pericardial, visceral and liver fat were estimated by magnetic resonance imaging. Carotid intima‐media thickness and distensibility were measured by ultrasound.A 1‐standard‐deviation‐score (SDS) higher body mass index was associated with higher carotid intima‐media thickness  and lower distensibility . These associations tended to be similar for lean mass index. A 1‐SDS higher fat mass index was associated with lower carotid intima‐media thickness  and lower distensibility . A 1‐SDS higher liver fat fraction was associated with lower carotid intima‐media thickness  and lower distensibility . We observed similar associations for visceral fat.At school age, lean and fat mass seem to be differentially related to carotid intima‐media thickness but not distensibility. Arterial development might be affected by lean mass, general and specific fat mass. CIconfidence intervalDXAdual energy x‐ray absorptiometryMRImagnetic resonance imagingSDstandard deviationSDSstandard deviation score1Higher body mass index seems to be a risk factor for higher carotid intima‐media thickness and lower carotid distensibility, two markers of arterial structure and function, respectively.In a population‐based prospective cohort study among 4728 children, we aimed to examine the associations of specific measures of body fat distribution, pericardial fat, visceral fat and liver fat mass, assessed by dual energy X‐ray absorptiometry and magnetic resonance imaging, with carotid intima‐media thickness and distensibility. Also, we examined whether these associations were independent of lean mass and fat mass.22.1This study was embedded in the Generation R Study, a population‐based prospective cohort study from foetal life onwards in the city of Rotterdam, the Netherlands.2.22) and subsequently sex‐ and age‐adjusted standard‐deviation‐scores (SDS), based on Dutch reference growth charts .2) and fat mass index as total fat mass (kg)/height (m4). We divided pericardial and visceral fat mass (kg) by height (m3) to obtain pericardial and visceral fat index, respectively.At the age of 10 years, children were invited to our research facility.2.3−1 × 10−3) as outcomes of interest. In a reproducibility study, the interobserver and intraobserver intraclass correlation coefficients were >0.85.As described in detail previously, we measured common carotid artery intima‐media thickness and distensibility using the Logiq E9  device.2.4We constructed a directed acyclic diagram Figure . Potenti2.5t‐tests, Mann–Whitney tests and Chi‐square tests. Second, we examined correlations of exposures and outcomes. Third, we used linear regression models to assess the cross‐sectional associations of body mass index, lean mass index, fat mass index, android‐gynoid ratio, pericardial fat index, visceral fat index and liver fat fraction with carotid intima‐media thickness and carotid distensibility at age 10 years. For each of these exposures, a separate model was constructed. To compare effect estimates, we analysed continuous exposures and outcomes in SDS, after natural log transformation carotid distensibility, which had a skewed distribution before transformation. The basic models were adjusted for sex and age at outcome measurement. The confounder models were additionally adjusted for child ethnicity and maternal age and education. Fourth, we performed several sensitivity analyses. We combined lean mass and fat mass index in one model to control for their effect on each other . We only observed a statistically significant interaction between lean and fat mass for carotid distensibility (p = 0.05). We used conditional regression analyses to examine whether the associations of regional body fat measures with carotid intima‐media thickness and distensibility were independent of lean mass index and/or fat mass index. We constructed fat mass variables that are statistically independent of lean mass index and fat mass index, respectively, allowing simultaneous inclusion in multiple regression models. Details are presented in the p < 0.05 and p < 0.01.First, we performed a nonresponse analysis by comparing characteristics of children with and without carotid artery ultrasound data using Student's 33.1−1 × 10−3. Compared with children with carotid artery measurements, those without outcomes on average were older when they visited the research centre and had less pericardial fat and liver fat . Fat mass index and android‐gynoid ratio were both inversely associated with carotid intima‐media thickness  and distensibility . Basic models showed similar results . Also, liver fat fraction was negatively associated with carotid intima‐media thickness and distensibility . Basic models showed similar results (Table Table ts Table .3.4n = 2135) were largely similar , the Netherlands Organization for Scientific Research (NWO), the Ministry of Health, Welfare and Sport and the Ministry of Youth and Families. Vincent W.V. Jaddoe received funding from the European Research Council (ERC‐2014‐CoG‐648 916). The project was supported by funding from the European Union's Horizon 2020 research and innovation program under grant agreements No 733206 (LifeCycle) and 874 739 (LongITools). Romy Gaillard received funding of the Dutch Heart Foundation (grant number 2017T013), the Dutch Diabetes Foundation (grant number 2017.81.002), the Netherlands Organization for Health Research and Development .No conflict of interest was declared.Vincent W.V. Jaddoe was responsible for conceptualization and design of this study. Giulietta S. Monasso analysed the data. Giulietta S. Monasso and Vincent W.V. Jaddoe interpreted the data. Giulietta S. Monasso wrote the original draft of the manuscript under the supervision of Vincent W.V. Jaddoe and Susana Santos, Carolina C.V. Silva, Edwin Oei, Romy Gaillard and Janine F. Felix were major contributors. All authors read and contributed to the preparation of the final manuscript. All authors read and approved the final manuscript.Data S1. Supporting information.Click here for additional data file.


Multikinase inhibitors (MKIs) represent the main treatment options for advanced hepatocellular carcinoma (aHCC). However, accessibility in developing countries is limited. A chemotherapy, Fluorouracil and Oxaliplatin (FOLFOX), offers a less expensive treatment. Therefore, this study sought to compare the clinical effectiveness of FOLFOX with Sorafenib as a first‐line treatment for aHCC in real‐life practice.A retrospective aHCC cohort from four Thai hospitals was investigated for patients who received FOLFOX or Sorafenib between 2013–2019. Multiple imputation by chained equations addressed missing covariate data in a treatment effect model using Weight‐adjusted‐censoring inverse‐probability‐weighted regression adjustment; overall survival (OS) and progression‐free survival (PFS) were estimated.n = 382] and FOLFOX [n = 122]). The treatment effect model estimated a median OS for Sorafenib and FOLFOX of 11.38 and 8.22 months, representing a significantly shorter OS  of −3.16  months for FOLFOX, p = 0.042. A significant shorter median PFS of FOLFOX to Sorafenib of −2.13  months, p < 0.001, was reported.A total of 504 patients were included, (Sorafenib [Despite significantly shorter median OS and PFS than Sorafenib, FOLFOX still extended OS by 8.22 months. This evidence may offer clinical utility to physicians considering treatment options for aHCC in low resource settings. Hepatocellular carcinoma treatment in limited resource countries was limit due to cost. Real‐world evidence reflects clinical effectiveness in general practice. Even though FOLFOX had significant shorter survival than Sorafenib, but FOLFOX still extended median overall survival by 8.2 months. Overall survival (OS) is a universally accepted direct measure of clinical benefit that represents the duration of patient survival from the time of treatment initiation. Progression‐free survival (PFS) is a direct or surrogate measure of clinical benefit representing the time from treatment initiation until disease progression or worsening. Findings from a pivotal HCC trialAlthough Sorafenib and Lenvatinib are considered standard treatments for intermediate and advanced HCC in western countries,As Sorafenib is the recommended treatment option for advanced HCC according to most international treatment guidelines,2A multicenter retrospective cohort of advanced HCC patients were recruited from four study hospitals, i.e., Ramathibodi Hospital, Maharaj Nakorn Chiang Mai Hospital, Lampang Cancer Hospital, and Vajira Hospital. Medical records between January 2013 to December 2019 were screened and patients were included if the following inclusion criteria were met: aged 18 years or older, pathologically or clinically confirmed HCC diagnosis , and received any first‐line systemic therapy including Sorafenib or Oxaliplatin‐based chemotherapy (FOLFOX). Patients whose medical records were not available for review were excluded.Criteria in Solid Tumors version 1.1.Demographic, clinical, radiological, and laboratory data were retrospectively collected and reviewed. HCC diagnosis and treatment decisions were made by physicians at each study hospital in light of health insurance coverage or patient willingness to pay. Treatment details and response to treatment, defined by radiography, were collected and categorized according to Response Evaluation Treatments of interest included Sorafenib and FOLFOX. Sorafenib was administered by daily dose until disease progression while FOLFOX was intravenously infused fortnightly until either disease progression or unaccepted toxicity was reached. Dosage for both drugs was adjusted by primary physicians in each hospital according to patients' performance status and comorbidities.OS was the primary outcome of interest defined as time from treatment initiation until death from any cause. A secondary outcome was PFS, defined as the time from treatment initiation to progression of disease or death. Patients' status  was verified by death certificate from the Ministry of Interior up to 31st December 2020. Disease control rates (DCR) were defined as a complete response, partial response, or stable disease as their best response. Adverse events (AEs) of interest were classified according to Common Terminology Criteria for Adverse Events version 5.0.The study protocol was approved from Ethics Committee of all study centers before starting data collection and management. .2.1t‐test or Kruskal‐Wallis test for continuous variables, as appropriate.Baseline characteristics were described by frequency and percentage for categorical variables and mean and standard deviation or median and range for continuous variables as appropriate. These characteristics were compared between FOLFOX and Sorafenib groups using Chi‐square or Fisher's exact test for categorical variables and student n = 50) was set to cover the highest fraction of missing information.Missing data was assumed as missing at random (MAR) and imputation using the Multiple Imputation Chained Equation (MICE) was performed. Logit, multi‐logit, and interval‐regression equations were used to impute binary, categorical, and continuous variables, respectively  was applied to estimate median OS and PFS for each treatment. Three models were constructed, i.e., treatment assignment, outcome, and censored models. For a treatment model, logistic regression was used to identify predictive factors associated with treatment assignment. For censored and outcome models, a parametric survival analysis with appropriate survival distribution according to the lowest Akaike information criterion was used to identify predictive factors. For each model, an initial univariate regression analysis was performed for each demographic, clinical, and baseline laboratory variable. Subsequently, a multivariate model with backward elimination was used to select significant co‐variables in each model. The conditional independence assumption, overlap assumption, and correct adjustment for censoring assumption were evaluated. DCR and AEs (any grade and grade ≥ 3) were described as the number of patients affected and percentage by treatment groups. All statistical analysis was undertaken using Stata software version 16 (Stata Crop). A 3A total of 504 patients were enrolled, with 382 patients receiving Sorafenib and 122 receiving FOLFOX. Baseline characteristics differed significantly between both treatment groups, see Table Missing data was as high as 45.6% for smoking status, followed by alcohol use (35.7%), Eastern Cooperative Oncology Group performance status 32.5%), AFP (19.8%), HCV infection (19.8%), HBV infection (9.5%), and creatinine (5.8%), see Table .5%, AFP A treatment assignment model was constructed with only four significantly associated covariates retained in the model, including region, health coverage scheme, Child‐Pugh classification, and AST, see Table p = 0.042, see Table At the end of follow up (31st December 2020), 464 out of 504 patients had died with a median follow‐up time of 5.72 (range: 0.20 to 86.75) months. Kaplan–Meier survival curves were constructed Figure  indicatip < 0.001, see Table For PFS, 303 patients had disease progression while 182 patients died; 15 patients were still under follow‐up or continuing treatment at the close of the study period. Unadjusted PFS curve by Kaplan–Meier method was constructed by Sorafenib and FOLFOX groups Figure  indicatip = 0.14). Serious AEs, grade 3 or higher, was lower for Sorafenib than FOLFOX (10.5% vs. 15.6%) but again this was not significant (p = 0.13). More hematologic AEs were observed in the FOLFOX treatment group, along with nausea, vomiting and neuropathy, while patients in the Sorafenib group were more likely to suffer diarrhea and hand/foot skin reactions.Of the 504 patients, 355 patients were evaluated for response to treatment, with 149 patients not evaluated representing 25% and 42% of the Sorafenib and FOLFOX groups respectively Table . DCR occ4This retrospective cohort of advanced HCC patients included real world data from 504 patients and compared relative treatment effects between Sorafenib and FOLFOX. The treatment effect comparisons using WAC‐IPWRA estimators identified significantly shorter OS and PFS of three and 2 months respectively for FOLFOX compared to Sorafenib, which had median OS and PFS values of 11.4 and 5.5 months, respectively. Furthermore, the FOLFOX DCR was also approximately 10% lower compared to that of Sorafenib. While overall AEs were almost 8% lower in the FOLFOX treatment group compared to Sorafenib, serious AEs were slightly higher in FOLFOX, although neither was significant.Baseline demographic characteristics were comparable to previous studies, i.e. predominantly male (65%–90%) and middle‐aged (50–68 years).The median OS and PFS of FOLFOX from a phase 3 RCTOur study had several strengths. Previous RCTs have compared MKIs to other MKIs or placebo, but there have been no direct comparisons with chemotherapy; this may be due to Sorafenib has been approved by the FDA as the standard first‐line therapy since 2007, which was before the EACH trialGiven the nature of our retrospective cohort study design, we were unable to avoid the issue of missing data. Despite addressing this concern through MICE approaches which assumes missingness is completely at random, MAR, or not at random; each of which could not be determined by statistical means. However, we assumed that the missingness was more likely to be related to the available data observed, i.e., MAR, and so MICE imputation models were constructed based on clinical outcomes  plus additional available covariate data making the MAR assumption more probable.In summary, this study used real world practice data with counterfactual analysis methods to simulate an RCT of clinical effectiveness between FOLFOX and Sorafenib in advanced HCC patients. Despite a significant 3 and 2 month reduction in median OS and PFS values for FOLFOX compared to Sorafenib, FOLFOX led to reasonable OS of 8.2 months, with no significant difference in the rate of AEs. This evidence may be especially useful for physicians considering potential treatment options for advanced HCC patients in resource limited settings.Songporn Oranratnachai: Conceptualization, study design, project management, data collection and management, data analysis, interpretation, Writing – initial draft, and contributed to every draft thereafter. Sasivimol Rattanasiri: Supervision, Writing – review & editing. Amarit Tansawet: data collection. Nilubol Raunroadroong: data collection. Ekaphop Sirachainan: Supervision, study design, data collection, interpretation, writing – critically review & editing. John Attia: Supervision, Writing – critically review & editing. Gareth J. McKay: Supervision, Writing – critically review & editing. Ammarin Thakkinstian: Supervision, study design, data analysis, Writing – critically review & editing.This research did not receive any specific grant from funding agencies in the public, commercial, or not‐for‐profit sectors.All authors declared no known conflict of interests or personal relationships that could have appeared to influence the work reported in this paper; except AT received grant from the National Research Council of Thailand (NRCT: N42A640323). The grant sponsor had no role in the design or conduct this study.The study protocol was approved from Ethics Committee of all study centers. .Table S1Table S2Table S3Table S4Figure S1Figure S2Figure S3Click here for additional data file.