For fortifiable wheat flour, the FAPQ estimated considerably lower mean intakes compared to 24HRs for children and mothers , while the SQ‐FFQ estimated slightly higher mean intakes . For fortifiable oil, the FAPQ estimated considerably higher mean intakes compared to 24HRs for children and mothers . The SQ‐FFQ, but not the FAPQ, generated useful information on fortifiable food consumption that can inform fortification programme design and monitoring decisions in the absence of more detailed individual‐level data. Potential adaptations to improve the FAPQ, such as additional questions on foods prepared away from home and usage patterns, merit further research.Information on fortifiable food consumption is essential to design, monitor and evaluate fortification programmes, yet detailed methods like 24‐h recalls (24HRs) that provide such data are rarely conducted. Simplified questionnaire‐based methods exist but their validity compared with 24HRs has not been shown. We compared two simplified methods  against 24HRs for estimating fortifiable food consumption. We assessed the consumption of fortifiable wheat flour and oil using a FAPQ and, for wheat flour only, a 7‐day SQ‐FFQ and compared the results against 24HRs. The participants included children 12−18 months  that provide such data are rarely conducted. Simplified questionnaire‐based methods exist but their validity compared with 24HRs has not been shown. We compared two simplified methods  against 24HRs for estimating fortifiable food consumption among Filipino children 12−18 months and their mothers and found that the SQ‐FFQ generated useful information on fortifiable wheat flour while the FAPQ systematically underestimated wheat flour and overestimated oil. Fortifiable  food consumption data are essential to design, monitor and evaluate fortification programmes, yet 24‐h recalls (24HRs) that provide such data are rarely conducted.Simplified methods, such as targeted food acquisition and purchase questionnaires (FAPQs) and semiquantitative food frequency questionnaires (SQ‐FFQs), exist but their validity compared to 24HRs has not been shown.Among Filipino children 12−18 months and their mothers, the SQ‐FFQ generated useful information on fortifiable wheat flour consumption while the FAPQ systematically underestimated wheat flour and overestimated oil.Further research could strengthen the FAPQ to better capture foods prepared away from home and usage patterns. Among studies that applied the AME method to HCES data to assess intake of potentially fortifiable staple foods compared with 24‐h recalls or other reference methods, wheat flour intake was consistently underestimated while agreement varied for other foods  using three dietary assessment methods. These were: two simplified methods  and a detailed dietary assessment approach, which included multiple 24‐h recalls and (among children only) observed weighed food records. In this article, we compare the results of the two simplified methods against those from the detailed dietary assessment as the reference method and discuss the utility of these methods to generate data for fortification programme decision making.22.1n = 150 total) would be needed. A more detailed description of the study design and sample size is reported elsewhere  in Mandaluyong City in the National Capital Region of the Philippines. Children were categorised into one of three groups at the time of enrolment: (1) likely high retinol intake (>600 µg/day) and receipt of VAS in the past 30 days; (2) likely high retinol intake (>600 µg/day) and receipt of a VAS in the past 3−6 months; or (3) likely low/adequate retinol intake /d) and receipt of VAS in the past 3−6 months. Sample size was based on the detection of mean retinol intake >600 µg/day in the high‐intake groups . Assuming 80% power, alpha 0.05, and 25% attrition rate, 50 children per group  child 12−18 months of age, (2) mother 18−49 years of age, (3) mother and child living in the selected study communities for at least 1 year and planning to stay in the study area for the duration of the study, and (4) the child's receipt of VAS and estimated vitamin A intake were consistent with one of the groups described above. Exclusion criteria included: (1) child or mother had chronic disease or signs or symptoms of vitamin A deficiency, (2) the child had a weight‐for‐length 2.2In this study, we collected data on the consumption of fortifiable  wheat flour and oil using three methods: a FAPQ, 7‐day SQ‐FFQ and a detailed dietary assessment approach, which included multiple 24‐h recalls and (among children only) observed weighed food records Table . These fOn Day 0 of the study, the mother of the child completed the FAPQ and SQ‐FFQ. The FAPQ collected household‐level information on general use and acquisition  and/or purchases of fortifiable wheat flour and oil (in their raw forms) along with information on the age and sex of all household members. The SQ‐FFQ collected individual‐level information on the consumption of fortifiable wheat flour‐containing foods in the last 7 days from a list of 25 items for both the child and the mother. For food items consumed, trained interviewers asked the mother to report the frequency of consumption over the past 7 days and estimate the usual portion size consumed using a photo album of various portion sizes for each food item. Fortifiable oil consumption was not assessed using the SQ‐FFQ method due to the difficulty of assessing amounts consumed in prepared foods obtained outside the household. The questionnaires were developed based on modules from the FACT household questionnaire template   for all items regardless of source   were calculated from recipe information. We then summed the resulting grams of fortifiable wheat flour and oil for all food items for each individual on each day to obtain the cumulative total grams of each fortifiable food consumed per person per day. We adjusted the values for within‐person variation to estimate usual intake distributions of fortifiable wheat flour and oil by applying the amount‐only National Cancer Institute method using the Simulating Intake of Micronutrients for Policy Learning and Engagement (SIMPLE) macro  and SAS version 9.4 (SAS Institute Inc.). We calculated means, medians, and percentiles of fortifiable food consumption estimates from the three dietary assessment methods. With the sample size of 123 participants, we were powered to be able to estimate mean consumption with a 95% confidence interval with ± 0.19 standard deviations, a relatively precise interval for interpreting average consumption. For the FAPQ and SQ‐FFQ methods, values >3 SDs from the mean were considered outliers and excluded . Additionally, 24‐h recall observations that were missing a corresponding FAPQ or SQ‐FFQ observation for comparison were excluded .We qualitatively compared the distributions of fortifiable food consumed as estimated by the FAPQ and SQ‐FFQ methods with those from the 24‐h recall reference method. For wheat flour, we also examined and compared the food sources as a percentage of total fortifiable wheat flour consumption to understand potential sources of differences between the SQ‐FFQ and 24‐h recalls. We did not do formal statistical significance testing to compare the individual‐level estimates of consumption from the FAPQ and SQ‐FFQ methods with those from the 24‐h recalls because the 24‐h recall usual intake estimates are intended to be interpreted only at the population level. Moreover, the interpretation of similar data for the purpose of designing and monitoring food fortification programmes is typically done at the population level.2.5Clinicaltrials.gov (NCT03030339). All study procedures were explained to mothers at the time of enrolment and the mother provided written informed consent for herself and the child to participate.This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Research Ethics Board of the University of the Philippines‐Manila, the Institutional Review Board of the University of California, Davis, and the Institutional Review Board of Newcastle University, and it is registered on 3A total of 123 child−mother pairs were enroled in the main study. All 123 children and 117 mothers completed the 24‐h recalls, and 116 child−mother pairs completed the FAPQ and the SQ‐FFQ. On average, children were 14.4 months of age, mothers were 28 years of age, and 50% of children were breastfed at the time of the study. Additional child, maternal, and household characteristics are reported elsewhere  and other foods . The ‘other’ category comprised ≤5% of total fortifiable wheat flour consumed, indicating that the SQ‐FFQ captured the major sources of dietary fortifiable wheat flour in this population.The sources of fortifiable wheat flour  estimated by the SQ‐FFQ were generally similar but varied for some food groups when compared to those from the 24‐h recalls Figure . Specifi4We compared two simplified dietary assessment methods  against 24‐h recalls as the reference method for estimating fortifiable food consumption among young children (12−18 months) and their mothers (18−49 years) in Mandaluyong City, Philippines. According to the 24‐h recalls, mean usual fortifiable wheat flour intake was 14.1 and 42.3 g/day among children and mothers, respectively, and mean usual fortifiable oil intake was 1.8 and 6.1 g/day, respectively. We found that the FAPQ method systematically underestimated fortifiable wheat flour intakes (by more than six times) and overestimated fortifiable oil intakes (by 2−2.5 times) compared to 24‐h recalls while the SQ‐FFQ mean estimates for fortifiable wheat flour were 11%−22% higher, and median estimates were within 5%−7% compared to those from 24‐h recalls.4.1For fortifiable wheat flour, the substantial and systematic underestimation of intakes by the FAPQ compared to the 24‐h recalls was largely due to the questionnaire excluding measurement of food products made from fortifiable wheat flour that are purchased and/or consumed outside the household. In this study, the FAPQ only captured the quantity of the food item acquired or purchased in its raw form . While this works reasonably well in contexts where most foods are prepared in the home, the approach may have limited utility in contexts where prepared food products containing wheat flour are commonly purchased. This was the case in the current study, which took place in an urban setting in the Philippines, where 64% of households reported not using fortifiable wheat flour at home to prepare foods (and thus were assigned zero for amounts consumed), yet the SQ‐FFQ and 24‐h recall results confirmed that wheat flour is commonly consumed as an ingredient in other foods. The most consumed foods containing fortifiable wheat flour were breads and noodles, which are typically purchased already prepared and are not captured by this specific FAPQ version. Other studies in Cameroon, Uganda and Bangladesh that applied the AME method to HCES data on acquisition and purchase of potentially fortifiable wheat flour included questions on both raw wheat flour and common wheat flour‐containing products , but similarly found that the HCES data underestimated total wheat flour consumed compared to reference methods  among children under 5 years and women of reproductive age  and/or patterns of intrahousehold food distribution that do not correspond to the assumptions of the AME method. The AME method assumes all fortifiable oil acquired is consumed by the members in the household yet in some contexts oil is discarded or reused when preparing foods, which would lead to overestimations of intake. Additionally, the AME method assumes that food is distributed within a household in accordance with the individual's proportion of total household energy requirements based on age and sex. However, this is not always the case, particularly with young children who potentially consume less from the family meals given they are often breastfed and/or receive other complementary foods . In some cases, fortifiable food consumption data can also be used to inform fortification levels in selected foods  to estimate additional micronutrient intakes and  the extent to which they fill identified gaps in the population. While the range of fortifiable wheat flour intakes varied somewhat between the SQ‐FFQ and 24‐h recalls, the mean and median  estimates did not differ greatly suggesting random error may contribute to observed differences. As a result, the two methods would yield similar mean and median estimates of additional micronutrient intakes and thus similar conclusions regarding average programme performance and potential for impact regardless of the fortification level applied. Conversely, the large and systematic variability between the FAPQ and 24‐h recall intake estimates for both fortifiable wheat flour and oil suggests that true consumption is not likely possible to determine through this method in its current form as additional micronutrient intakes could be greatly over or underestimated. This could result in overly high or low estimates of micronutrient intakes from fortified foods and thus differing expectations about the potential impact of the fortification programme. That said, FAPQ data are likely still better than national food supply data , which are often used to estimate potential micronutrient intakes in the absence of individual‐level data, as those do not account for household food acquisition or purchases or permit assessment of subnational variation in use of fortified foods.4.4There were some limitations to this study. The 24‐h recall method was used as the reference method against which the results of the simplified methods were compared; however, it is not a gold standard and has its own sources of error  (Hébert et al., 5Simplified dietary assessment methods, such as FAPQs and SQ‐FFQs, are alternatives to more detailed methods for generating data on fortifiable food consumption with reduced effort and cost. While this study and others have shown there are still some important differences in the results, the resulting fortification programme decisions may still be similar for some methods and foods (Dary & Jariseta, Valerie M. Friesen, Mduduzi N.N. Mbuya, Lynnette M. Neufeld, Frank T. Wieringa, and Reina Engle‐Stone designed the research; Ame Stormer, Georg Lietz, Marjorie J. Haskell, and Reina Engle‐Stone oversaw implementation of the field study; Jody C. Miller, Ryan B. Bitantes, Maria Fatima Dolly Reario, Mario V. Capanzana, and Carl Vincent D. Cabanilla conducted the research; Valerie M. Friesen, Jody C. Miller, Charles D. Arnold analysed the data; Valerie M. Friesen wrote the paper; Valerie M. Friesen, Charles D. Arnold, Mduduzi N.N. Mbuya, Lynnette M. Neufeld, Frank T. Wieringa, Georg Lietz, Marjorie J. Haskell, Reina Engle‐Stone had primary responsibility for data interpretation; Valerie M. Friesen and Reina Engle‐Stone had primary responsibility for final content; all authors: read and approved the final manuscript.The authors declare no conflict of interest.


Patients with advanced incurable cancer face difficult decisions about palliative treatment options towards their end of life. However, they are often not provided with the appropriate information and support that is needed to make informed decisions. This review aimed to identify contexts and mechanisms associated with communication tools, patient decision‐aids and shared decision‐making (SDM) approaches that influence patient outcomes.We used a realist review method to search for published studies of patients (adults > 18) with advanced cancer who were expected to make a decision about palliative treatment and/or supportive care in consultation with healthcare practitioners. We appraised and synthesised literature describing the contexts of (when and how) decision aids and SDM approaches are used, and how these contexts interact with mechanisms (resources and reasoning) which impact patient outcomes. Stakeholders including academics, palliative healthcare professionals (HCPs) and people with lived experience of supporting people with advanced incurable cancer contributed to identifying explanatory accounts. These accounts were documented, analysed and consolidated to contribute to the development of a programme theory.From the 33 included papers, we consolidated findings into 20 explanatory accounts to develop a programme theory that explains key contexts and mechanisms that influence patient and SDM. Contexts include underlying patients' and HCPs' attitudes and approaches. These need to be understood in relation to key mechanisms, including presenting information in multiple formats and providing adequate time and opportunities to prepare for and revisit decisions. Contexts influenced mechanisms which then influence the levels of patient decisional satisfaction, conflict and regret.Our programme theory highlights mechanisms that are important in supporting shared treatment decisions for advanced noncurative cancer. The findings are informative for developing and evaluating interventions to improve understanding and involvement in SDM for patients with advanced incurable cancer.We included patient and public involvement (PPI) representatives in four stakeholder meetings. PPI helped to define the scope of the review, identify their unique experiences and perspectives, synthesise their perspectives with our review findings, make decisions about which theories we included in our programme theory and develop recommendations for policy and practice and future research. These treatments can kill cancer cells to improve symptom control and change the course of the disease to extend lifeWhen delivered early (90 days before death), a palliative/supportive care‐only approach can help reduce symptom burden and improve mood and quality of life for patientsIt is imperative that all treatment and alternative care options are presented to patients so that they can be fully informed about the potential benefits and harms of treatments and alternative options before making treatment decisions. However, decisions regarding whether to start, continue palliative treatment or accept supportive and palliative care are complex for healthcare professionals (HCPs) and patients, as individual responses to treatments vary, are difficult to predict, and there can be uncertainty about prognosis.The National Institute of Clinical Excellence's guidance on improving supportive and palliative care for adults with cancer recommends that patients should be involved in decisions about their treatment and care along the cancer pathway using a shared decision‐making (SDM) approach.Decision support tools (decision aids) can be used to provide information about the risks and benefits of treatments and enable patients to reflect on and communicate their preferences to HCPs and participate in SDM.1.1Our aim was to use a realist approach to understand how SDM approaches and patient aids influence patients with advanced cancer when deciding on palliative treatments and care.We aimed to identify recent literature on SDM, decision support tools and communication tools used for all types of advanced cancer and to develop a programme theory to explain their impact on patients' experiences of treatment decision‐making.Realist research typically seeks to answer ‘what works, for whom, under what circumstances?’, and ‘How?’, ‘Why?’ and ‘To what extent?’ does an intervention produce certain outcomes? Realist research focuses on developing theories to explain how different contextual factors influence mechanisms (related to resources put in place or the way that people reason) and how they might lead to different or similar outcomes.contexts  in which our intervention of interest . Then, identify how contexts influence mechanisms  to impact patient experience outcomes, such as patient's perceived quality of their decision‐making experience and satisfaction with their decision.Realist methods involve developing Context, Mechanism and Outcomes theories. This involves identifying how the different This realist review is registered on PROSPERO 2021 CRD42021251690.22.1We used realist review methodology to identify, appraise and synthesise diverse forms of evidence to generate theories about how patient aids and SDM approaches are used and what outcomes are achieved.2.1.1In line with realist review methodology we worked collaboratively with stakeholders  to produce findings that can be translated to service improvements and intervention development.2.1.2To help define the scope of the review and identify evidence to develop initial theories (step 2), we carried out a brief initial literature scoping exercise step 1). We searched the literature using google scholar and were also recommended papers by our review team and stakeholders. Findings were extracted from studies about palliative treatment decision‐making  which influenced mechanisms (m) such as patient's attitudes and understanding about choice, their role in decision making, and how informed and prepared they felt. In turn, these influenced outcomes (o) related to patients' level of involvement, their choices, their satisfaction with their choices and the consequences of their choices . We have illustrated our preliminary theories in our initial programme theory below , patients may perceive they have a valid role in decision‐making (m) and are more likely to be actively involved in decision‐making (o).2.1.4We included studies of patients (adults > 18) with advanced cancer  who were offered and expected to make a decision about noncurative treatment  and/or supportive care in consultations with healthcare practitioners. We also included studies about patients who were making decisions about ending chemotherapy. Our interventions of interest were patient aids, communication tools, question prompt lists, web‐based interventions, SDM approaches that support or contribute to informed decision‐making and patient participation in decision‐making about noncurative treatment. Our outcomes of interest were related to patient's experiences .2.1.5ClinicalTrials.gov  and World Health Organisation (WHO) International Clinical Trials Registry Platform (www.who.int/ictrp/en) for ongoing trials. M. E. and D. H.‐H. checked reference lists from primary studies and relevant systematic reviews were checked for further potentially relevant studies and carried out backward and forward citation tracking. Grey literature searches were carried out on Google Scholar and Google, University's Option Grid and the National Institute for Health and Care Excellence Evidence, UK National Health Websites and national and international government websites. We carried out an updated search in November 2022 using the same search strategy in Supporting Information: Appendix Search strategies were developed and searches were carried out by M. M. This initially included studies published from 2000 to April 2021 using the following databases: CINAHL (EBSCO), Cochrane Central (WILEY), Cochrane Library (WILEY), Embase (OVID), MEDLINE (OVID)PsycINFO (OVID), Social Science (PROQUEST) . Two reviewers (M. E. and D. H.‐H.) independently screened all the references by title and abstract to find articles that met our inclusion criteria . We created an abstract and full‐paper screening tool to screen for inclusion and rank each paper selected as ‘yes’ or ‘maybe’ and from one to four in terms of relevance to our review questions and initial programme theory  (see Supporting Information: Appendix 2.1.6contexts (If) that influence mechanisms (because) and lead to outcomes (then)  and discussed explanatory accounts frequently to enable refinement and consistency of application. When all data extraction forms were completed, there were 274 explanatory accounts drawn up.n = 290). This enabled us to refine explanatory accounts and develop new ones [Stakeholder/PPI meeting 2].As part of our stakeholder involvement process, we discussed explanatory accounts that we identified. Then, we co‐developed an additional 16 explanatory accounts with HCPs  and PPI representatives . The total number of explanatory accounts  to iteratively test these theories and build an overall programme theory.3n = 4570. After duplicates were removed (n = 3355), 3221 abstracts were excluded for not meeting the criteria and 134 full‐text papers were assessed for eligibility and n = 94 papers were excluded because they were ranked ‘likely irrelevant’. We selected 40 papers for data extraction based on our initial ranking of relevance. Then, seven were excluded after we identified that these papers did not contain enough relevant data to create theories. The final number of studies included in the first search of the review was 33, this was after an extensive search for explanatory accounts that were relevant to the review questions. Our updated search in November 2022 identified 419 records, after the removal of duplicates. We screened these records and read 14 papers in full that were relevant to the inclusion criteria. No new papers provided were included in the review. The results from search one and two and the screening process are outlined below in the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses diagram  and palliative care‐only decisions. One review paper on decision aids used for end‐of‐life decisions. Most papers discussed chemotherapy, one paper studied radiotherapy and one paper studied immunotherapy  and mechanisms (m) and how they influence a range of different outcomes (o) for patients are reflected in the list of theories . HCP support contexts include communication approaches  (theories 15–17 and 20), the provision of empathy (theory 16) and role perception (theory 15) within the particular decision‐making context.3.43.4.1Patients need to understand that there will be a choice involved when discussing the risks and benefits of treatments and to be clear about their and the clinician's roles in treatment decision making (theory 1). Patients also need time to be prepared and planned for conveying their information needs and communication preferences to HCPs and engaging with the terminology that will be used (theory 19). Preparation time may also be useful to support patients by speaking with family and involving them in their decision‐making (theory 11). Additionally, patients could benefit from a guide of timescales associated with information exchange and treatment decision‐making (theories 10–14).3.4.2Providing patient aids in clear and multiple formats helps patients understand their options and engage in decisions (theories 7–9). Including palliative care and prognostic information and terminology in patient aids and involving palliative care specialists in developing patient aids and in discussions with patients to support patients with decision making about active treatment or palliative care, also helps patients make more informed decisions (theory 20). Providing training to HCPs on using SDM approaches is also essential to decision support (theory 18).3.4.3Supporting patients to reflect on previous treatment when engaging with treatment decision‐making and helping them understand differences in side effects and tolerance to treatment could help them understand the contextual differences when a new decision is presented. Enabling reflection on patients' personal information needs and preferences and communicating these to HCPs in consultations is essential in considering treatment and alternatives .3.4.4We include further reflection and evaluation of prior treatment experiences and decisions (theories 3 and 4). We also include mechanisms related to awareness and consideration of future decisions and the opportunity for patients to reflect on and communicate their changing needs and decisions.3.4.5Treatment decisions are not necessarily definitive in the programme theory, they are made and can be reflected on and changed or renegotiated with the support of HCPs.3.5Intermediate outcomes for patients are that they are better prepared for engaging with information and treatment decision making. They should also be then better engaged and informed and able to reflect on their personal goals of decision‐making before making a treatment decision. The outcomes of their decision can then result in regret, satisfaction or conflict .Subsequently, we presented and discussed inferences made in the programme theory to our public involvement representatives and stakeholders to ensure their perspectives were included in the programme theory and ask for their perspectives on the importance of the finding and the ways findings could be used to influence changes in policy and practice. It was noted that there could be an opportunity for patients to be more prepared to ask questions and have patient‐centred conversations. Stakeholders also referred to a need to understand hcp motivations to embrace changes in communication styles. We were reminded by our PPI representatives to ensure that our programme theory and recommendations took into account family members also present in consultations. Together with our stakeholders, we developed ideas for intervention components that might be successful for different cancer patients and in different settings, that is, cancer clinics/appointments) [Stakeholder/PPI involvement meeting 4].44.1Our review findings show the range of contexts and mechanisms that can potentially improve patients' experiences of treatment decision making when considering treatment options for advanced noncurative cancer. These include clinician's positive attitude and behaviour towards SDM; patients' skills in engaging with information and reflections on prior treatment experiences; the content and format of patient decision aids ; involvement from palliative care specialists and the timing of delivery and the time provision before decision making. Positive outcomes for patients included understanding information; acceptability of using a decision aid; ability to participate in SDM; the level of control they feel they have in the decision‐making process and whether they feel less conflict and more satisfaction regarding their decision.4.2The findings illustrate that using appropriately designed decision support tools can improve knowledge about options, risks and outcomes, and also reduce decisional conflict and regret for patients, reflecting previous studies.We found that multi‐component  decision support interventions delivered by HCP are associated with mechanisms that lead to positive outcomes in supporting patients to understand and engage in SDM. This reflects previous research that emphasises the need for decision aids to be accompanied by HCP advice and support during the SDM processPrevious studies have provided evidence that Internet/digital delivery can provide the right information (rapidly updated), to the right person (tailored), at the right time (the appropriate point in the decision‐making process).4.3time which is suitable and personalised to their individual needs, and is accessible in multiple formats. Patients can benefit from the information provided through decision support tools and discussions with HCPs that are tailored to their prognosis and explain the benefits and harms of treatment options.The context‐focused findings of our review can inform policies, strategies and guidance, relating to SDM and patient involvement.Patients benefit from honest and open discussions regarding their individual treatment outcomes and need balanced and understandable information regarding their treatment options.Our review highlights that palliative care specialists should be involved in the decision support process (including the development of decision and communication tools), integrating palliative care support more consistently within the patient pathway can lead to improvements in quality of life; quality of death and potentially slow down cancer progression and prolong length of life.4.4The review provided insights into what works when and for who in relation to interventions for advanced cancer. Stakeholder involvement provided in‐depth practical knowledge and experience throughout the realist review process, which provided regular opportunities for reflection and refinement of the theories relating to first‐hand experiences.http://nihr.ac.uk/pi-standards/home)Including PPI representatives in stakeholder meetings  supported the study and carried out the validation of the findings. All authors reviewed and commented on the drafts of this manuscript. All authors read and approved the final manuscript.The authors declare no conflict of interest.Supporting information.Click here for additional data file.Supporting information.Click here for additional data file.Supporting information.Click here for additional data file.Supporting information.Click here for additional data file.Supporting information.Click here for additional data file.


The demand for induced pluripotent stem cells (iPSC)‐derived retinal organoid and retinal pigment epithelium (RPE) models for the modelling of inherited retinopathies has increased significantly in the last decade. These models are comparable with foetal retinas up until the later stages of retinogenesis, expressing all of the key neuronal markers necessary for retinal function. These models have proven to be invaluable in the understanding of retinogenesis, particular in the context of patient‐specific diseases. Inherited retinopathies are infamously described as clinically and phenotypically heterogeneous, such that developing gene/mutation‐specific animal models in each instance of retinal disease is not financially or ethically feasible. Further to this, many animal models are insufficient in the study of disease pathogenesis due to anatomical differences and failure to recapitulate human disease phenotypes. In contrast, iPSC‐derived retinal models provide a high throughput platform which is physiologically relevant for studying human health and disease. They also serve as a platform for drug screening, gene therapy approaches and in vitro toxicology of novel therapeutics in pre‐clinical studies. One unique characteristic of stem cell‐derived retinal models is the ability to mimic in vivo retinogenesis, providing unparalleled insights into the effects of pathogenic mutations in cells of the developing retina, in a highly accessible way. This review aims to give the reader an overview of iPSC‐derived retinal organoids and/or RPE in the context of disease modelling of several inherited retinopathies including Retinitis Pigmentosa, Stargardt disease and Retinoblastoma. We describe the ability of each model to recapitulate in vivo disease phenotypes, validate previous findings from animal models and identify novel pathomechanisms that underpin individual IRDs. Retinal organoids have become an exceedingly useful tool in recent years for understanding retinogenesis, particularly in the context of retinal disease. Pluripotent stem cells (PSCs) can be derived directly from somatic cells of affected patients, or alternatively, existing pluripotent lines can undergo gene editing to harbour mutations of interest. These PSCs can then undertake a directed differentiation to retinal tissues in vitro, specifically retinal organoids and retinal pigment epithelium (RPE), giving the investigator an abundance of disease‐relevant tissue to assay. There are several applications for the use of retinal organoids and RPE in the scientific study including disease modelling, understanding retinogenesis, drug screening and toxicological screening. This review aims to serve as a primer in the utility of retinal organoids and RPE, derived from PSCs, in the study of inherited retinopathies. Using retinal diseases, such as Retinitis pigmentosa, Stargardt disease and Retinoblastoma, we discuss how PSC‐derived retinal tissues can corroborate results from animal models and uncover novel molecular signatures of disease that may be crucial in developing therapies against inherited blindness. Animal models, particularly murine, have proven useful in informing us of conserved developmental processes across species. However, even though a large proportion of functional DNA sequences are highly conserved between mice and humans, the regulation and expression of these genes differ significantly, limiting their application in the study of human health and disease  from human somatic cells has greatly expanded opportunities for disease modelling, particularly in a patient‐specific context. These iPSCs are almost undisguisable from embryonic stem cells (ESCs) and retain the capability to become any cell type specified , Stargardt disease (STGD1) and Retinoblastoma (Rb). Evidence from the studies discussed in this review highlight the importance of iPSC‐derived retinal organoids and RPE in the apprehension of molecular signatures of disease during retinal development in utero which may inform future health screening, diagnoses and prognoses as well as potential prevention measures for vision loss.2With the use of PSCs, retinal organoids (ROs) or ‘mini‐retinas’ can be generated in vitro and remain stable for over 210 days in suspension culture. These 3D structures are highly reminiscent of the native retina which up to 38 weeks, develop at similar rates in utero . OVs continue to grow towards the surface ectoderm, which upon contact forms the lens placode. The resulting optic stalk attaching the OVs to the forebrain later becomes the optic nerve . However, this culturing method does not support the formation of RPE, a pigmented monolayer adjacent to the photoreceptors. RPE is crucial for the maturation of retinal neurons as well as for phototransduction with the recycling of proteins necessary for the visual cycle Strauss, . In diseDespite evident anatomical inadequacies, past studies have shown the true utility of the RO model in understanding the overarching developmental pathways involved in generating retinal tissue  was granted FDA approval in recent years FDA, . This isiPSC‐derived retinal models have the potential to offer us patient‐specific insights into the pathophysiology of every retinal disease in a cell‐specific manner. Using these tools, we can track the development of individual cells from the moment they are born until 38 weeks of comparable in utero retinogenesis. This enables us to dissect the influence of genetic mutations in retinal genes on functional networks in the retina to comprehend pathomechanisms of disease and uncover novel therapeutic targets. This literature review discusses three examples of retinal disease, where in vitro iPSC‐derived retinal models have been effective in broadening our knowledge of the retinal disease.44.1Retinitis Pigmentosa (OMIM #268000) is one of the most prevalent IRDs with an incidence of 1:4000 individuals worldwide  are amongst those genes implicated in adRP representing 15%–20% of cases in this cohort of RP. PRPFs are small nuclear ribonucleoproteins (snRNPs) that have a role in the formation and maturation of the spliceosome, a large macromolecular complex involved in the removal of introns and processing of pre‐mRNA to mature mRNA. PRPFs that have been associated with adRP, namely PRPF3, PRPF4, PRPF6, PRPF8, PRPF31, SNRNP200 and RP9, are involved in the formation of the tri‐snRNP, an essential element for the formation of the pre‐catalytic subunit (complex B) of the spliceosome. Mutations in the components of tri‐snRNP reduce the efficiency of spliceosome assembly and result in global dysregulation of splicing , a gene which encodes the PRPF31 protein, which is involved in U4/U6 snRNPs assembly  were related to pre‐mRNA and alternative mRNA splicing. Interestingly, the identification of long‐mutant PRPF31 mutation was confirmed with siRNA knockdown in a human RPE cell line which recapitulated the disease phenotype.In the same study, GO enrichment for RP11‐fibroblasts also showed significant differential exon usage for genes involved in ciliogenesis and maintenance, validating previous work which showed reduced cilia length and incidence in fibroblasts from RP11 patients  was corrected and then differentiated alongside RP11‐iPSCs. Genetic correction of this defect restored the phenotype of retinal cells with increased cilia length and incidence in both photoreceptors and RPE cells. Phagocytotic capacity of RPE cells was also restored along with apical‐basal polarity. This demonstrates that CRISPR/Cas9 gene editing in situ is a possible route to explore for therapeutic intervention of PRPF‐mediated retinal disease , a molecular chaperone involved in the repair of misfolded proteins  in the neural retina.It was clear that the cytoplasmic aggregates identified in RP11‐RPE were destined for degradation via the UPR pathway by the upregulation of FK1—a marker of ubiquitinated proteins, in the patient cell lines. Transmission electron microscopy (TEM) revealed the presence of multivesicular bodies and large vacuoles filled with electrodense material in RP11‐RPE. Evidence of debris was also observed in gaps between the cells suggesting these aggregates contribute to the disruption of tight junctions between cells.4.2.4In RP11‐ROs, a significantly high proportion of differentially expressed genes were identified. However, only those related to PRPF31 aggregation and photoreceptor function were considered. These included ER lumen, autophagy and lysosome, retinoid metabolism, visual perception, response to ER‐stress and UPR pathways. Generally, PRPF31 and numerous other snRNPs were significantly downregulated in RP11‐ROs. Particularly, NOVA1 and PTBP2, which are proteins involved in the modulation of neuronal‐specific genes in the brain and are vital for neuronal survival, were amongst the most significantly downregulated. This suggests defective mRNA metabolism in RP11‐ROs  stress. In normal scenarios, this mechanism is tightly transcriptionally regulated. However, if stresses are prolonged and acute, this can result in significant cell death , caspase‐like (PSMB9) and trypsin‐like (PSMB10) were significantly downregulated suggesting impaired proteasomal degradation in RP11‐RPE. As autophagy is often initiated in these scenarios, the expression of markers in each stage of autophagy was assessed. This revealed a block in late‐stage autophagy with the upregulation of several proteins including p62 and LC3‐II. These are conventionally associated with an inhibition of autophagosome degradation  is monogenic inherited retinopathy caused by bi‐allelic mutations in the ABCA4 gene  allows for insight into the effect of the mutation on the protein. If protein effects are demonstrated by the assay, the unsolved case can be reclassified as solved with high confidence. While PPCs are effective in confirming a splicing defect and serving their purpose in this context, they are not suitable in vitro model to fully characterise the impact of the mutation on other cell types of the retina. PPCs are an immature cell type cultured in isolation in a two‐dimensional format. Along with the loss of physiological context of the retina, ABCA4 is expressed specifically in the photoreceptor outer segment, which takes a minimum of 120–180 days in RO suspension culture to develop . We matured these organoids until day 230 and detected ABCA4 protein expression in nascent photoreceptor outer segments. We have also confirmed the expression of ABCA4 by Western blotting. With the use of a confirmed biallelic STGD1 control line, we showed reduced protein expression as expected from gene expression data in a study utilising the same iPSC line  is an intra‐ocular childhood cancer that initiates in the retina of developing eyes. The overall incidence of this condition is 1:15,000–20,000 globally, accounting for 9000 new cases each year in individuals <5 years of age Kivelä, . Rb is iRB1. Knudson in 1971 made the observation that Rb formation is dependent on two mutational events taking place in this gene and termed this the ‘two‐hit hypothesis’  pre‐disposing them to Rb. The second mutation occurs somatically in a susceptible cell of the retina (Mutation 2). In addition to increased risk for Rb development, individuals with constitutional mutation of Rb1 also have a predisposition to secondary cancers in other tissues  to regulate the G1 to S‐phase transition in the cell cycle. Specifically, pRB acts to repress E2F transcription factors which activate genes related to cellular proliferation. In response to mitotic signals in the environment, CDKs hyperphosphorylate pRB to relieve its repression on E2Fs and subsequently permit cell cycle entry. Considering the important role pRB plays in this process, it makes sense that loss of its function leads to uncontrolled cellular proliferation and the initial formation of benign tumours called retinomas. Increased cellular proliferation leads to increased genomic instability and enables the transformation of susceptible cells via the acquisition of secondary mutations in Despite the years of research and a number of studies on Rb, it remains an enigma as to why a ubiquitously expressed tumour‐suppressor gene results in a retina‐specific phenotype when defective. It has been suggested that this is likely due to specific characteristics of a susceptible cell in the retina. Identifying this cell has been somewhat challenging but numerous studies have pinpointed the cone precursor as the cell of origin. Early studies consistently saw the expression of key cone cell markers in low passage Rb cell lines  in Rb1 mutations were reprogrammed to iPSC and differentiated to 3D ROs using an optimised 3D retinal organoid protocol. ROs from each patient were matured for 45 days and at which point were dissociated and injected intravitreally into immunocompromised mice to investigate in vivo tumorigenesis. As expected, each mouse developed retinal tumours, distinct from teratomas. Whole‐genome sequencing revealed inactivation in the second allele of the RB1 gene with no other cancer gene aberrations , RPCs were the most common cell identified in a pool of RB tissues including orthotopic patient‐derived xenografts, healthy adult retinas, retinoblastomas and iPSC‐RBs, corresponding to 53% of the cells in this subset. This was closely followed by rod photoreceptors making up 31% of the total cells sequenced. An interesting observation they note is the hybrid gene expression phenotype displayed by individual RB tumour cells which are not present in normal retinogenesis. Their study suggests that the cell of origin is RPCs, and the hybrid gene expression observed can be explained by their multipotency in retinal development . The mutational status of these cell lines, alongside isogenic controls, allows for a thorough molecular investigation of Rb development and for the acquisition of novel insights regarding in vitro tumorigenesis.Many studies to date have focused on the end‐stage of tumour development in Rb. However, our research group is particularly interested in the transcriptional events taking place during cell state transitions that preclude Rb development (Rozanska et al., + Ki67+ cone precursor cells, and retinal progenitors in all RB1‐ROs—see Figure One key phenotype observed in our models was the significant decrease in amacrine cells observed alongside the increase in RXRƴThe cellular transformation was evident from the culturing of dissociated cells of RB1‐null ROs in soft agar, a gold standard assay for assessing the tumorigenic potential of a cell (Au—Borowicz et al., A novel aspect of this study was that RB1‐null ROs were cultured for long periods of up to 150 days, enabling an apt time frame for the appearance of tumorigenic properties in vitro. Such a model is not only invaluable for understanding the molecular pathogenesis of RB1 but also in the drug screening and toxicology profiling of candidate drugs for pre‐clinical trials.As a proof of principle drug screening experiment, 150‐day‐old RB‐null ROs were incubated with three different drugs commonplace in the treatment of RB: Melphalan, Topotecan and TW‐37 for 72 h. Quantitative immunofluorescence of resulting ROs revealed a significant decrease in the quantity of proliferating cone precursors at specific doses for each drug, validating the RB1‐ROs as a robust platform for drug screening.5iPSC‐derived retinal models have proven to be invaluable in the study of retinal diseases. This tool specifically gives insight into a window of development that precludes the onset of disease in humans. This time frame is often disregarded in the study of pathogeneses of retinal disease as disease phenotypes often present postnatally. With retinal disease, it is important to treat affected individuals before the onset of neuronal cell death as neurons are post‐mitotic and cannot regenerate. In that regard, it is important to interrogate the potential influence of mutations in retinal disease genes during the process of retinogenesis. There are likely clues hidden in the molecular signatures of these diseases during development which could provide novel disease biomarkers for prenatal screening or novel therapeutic avenues to explore, providing opportunities to prevent and treat the retinal disease before a loss of vision.This review provides ample evidence of the validity of retinal organoids for the study of retinogenesis as their ability to recapitulate many features of in vivo retinal disease. ROs can provide endless opportunities to study disease from a patient‐specific context, which is often not possible with animal models. However, like any model, ROs also present some limitations to their use. Retinal development continues postnatally. ROs do not offer this view of retinal disease, particularly in diseases that are age‐related—which need additional stressors to recapitulate in vivo phenotypes. ROs will likely not replace in vivo animal models completely but instead, serve as a tool to be used in conjunction with in vivo or in silico modelling of retinal disease. Further to this, many diseases involve both neural retina and RPE, but existing RO models are not able to produce anatomically correct and functional RPE in situ. This affects the maturation of photoreceptor outer segments and ultimately their functional capacity in terms of the light response. Future work is focused on developing co‐cultured models of ROs and RPE for the purpose of transplantation and more accurate disease modelling.


People with dementia sometimes refuse assistance with personal care activities such as washing or dressing. We aimed to investigate the factors associated with refusals of care in advanced dementia.n = 260, 130 dyads) in the UK. Mixed effects linear models were used to examine the effects of neuropsychiatric behaviours, ability with activities of daily living, professional input, co‐morbidities, psychotropic medications, environment modifications, and caregiver factors including type and training status on refusals of care. The Refusal of Care Informant Scale was used, range 1–13; higher scores indicate more refusal behaviours.A cross‐sectional study using informant‐based measures. Participants were people with advanced dementia and their caregivers (family carers or care‐home staff) . Higher agitation was associated with more refusal behaviours . No other statistically significant differences were found. There was no demonstrable evidence of differences in number of refusals of care between family and care‐home caregivers or between dementia‐trained or ‐untrained caregivers.Higher independence in activities of daily living was associated with less refusal behaviours  or dementia training status, indicating that current dementia training has no impact on refusals of care or may not be implemented as intended. Improving independence in activities of daily living and reducing agitations may help prevent refusals of care. To establish causality, future research should consider embedding these factors into interventions targeting refusal of care. Refusals of care occur when a person with dementia finds assistance with their basic activities of daily living, such as washing or dressing, unwelcome and demonstrates in some way that they are not happy to receive help.In advanced dementia, higher independence in activities of daily living was associated with less refusals and higher agitation was associated with more refusals.Caregiver setting (family or care home) or training in dementia (none or some) were not associated with refusals of care. We hypothesised that there would be differences in refusals of care between care settings (care home and family) and between caregivers with dementia training and those without (some family caregivers access dementia training and some care‐home staff do not). We theorised: (1) that as formal care staff in care homes were professional caregivers they would experience less refusals of care, and (2) that trained caregivers, irrespective of care setting, would experience less refusals of care.Ethical approval was sought and given from the Queen's Square Research Ethics Committee, London (reference: 251339).22.1A cross‐sectional study using informant‐based measures was used.Participants were recruited in dyads: a person with advanced dementia either supported at home or in a care home, aged 65 or over, receiving physical assistance with personal care activities such as washing or dressing and the family carer or care‐home staff member who regularly assisted them. Family carers were the primary caregiver for the person with dementia and were over the age of 18. Care‐home staff were usually assisting the person with dementia with their care at least six instances a week and were over the age of 18.To determine the eligibility criteria of advanced dementia, the Frontier Dementia Rating Scale (FRS),2.2People with dementia in England not living in care homes and their family carers were identified from either a local research‐team database or a national database called Join Dementia Research, where those registered had expressed an interest in being contacted about research opportunities. Written information was provided, and the first author discussed the research with potential participants.Care homes in the UK offer 24‐h accommodation, meals, and assistance with personal care either with or without qualified nursing staff. Care homes assisting people with dementia in the East of England were identified from the Care Quality CommissionWritten consent or advice was obtained for all participants. For people with dementia assessed as lacking the capacity to decide about whether to take part, in line with the Mental Capacity Act of England and Wales 2005,2.3d) of 0.5, for the difference of refusals between care‐home staff and family carers. A minimum sample of 128 dyads would detect a medium effect at 5% (two‐sided) level of significance with 80% power.Sample size was calculated a priori using GPower.2.4Data were collected in England between January 2019 and May 2021. Data collection was predominantly informant‐based and took place either face‐to‐face, over the telephone or online via Zoom with caregivers. Face‐to‐face data collection took place in family homes and in the care homes where the care‐home staff worked. Caregivers answered the first author's questions about the person with dementia and also filled in three self‐complete questionnaires about themselves . Dementia sub‐type was determined from people with dementia's General Practitioners (GPs). Consent to contact GPs for diagnoses was obtained at the time of study consent.2.4.1Refusals of care were assessed through the RoCIS,Caregiver type (care home or family) and dementia training  were assessed with a bespoke questionnaire; these two factors were our hypothesised main exposures of interest.Care setting was a grouping variable—either a care home or the family setting for each dyad. Each care home was defined as a cluster and all dyads from the family setting were assigned to one (family) cluster.Demographic details such as age, gender and ethnicity, and psychotropic medication use and health status over the last month were taken using a bespoke questionnaire.Neuropsychiatric symptoms were assessed using the 12‐domain Neuropsychiatric Inventory (NPI) Questionnaire .Agitation was assessed using the Cohen Mansfield Agitation Inventory (CMAI),Functional ability was assessed using the Alzheimer's Disease Cooperative Study Activities of Daily Living Inventory for severe dementia (ADCS‐ADLsev19).Environmental modifications were assessed using a reduced version of the Home Environmental Assessment Protocol for Dementia (HEAP) to determine the presence or absence of bedroom or bathroom modifications.Professional input, including any GP, nurse, medical, allied health professional, or hospital visit, in the last 3 months was assessed using a reduced version of the Client Service Receipt InventoryComorbidities such as liver disease, heart failure and cancer were assessed using the Charlson Comorbidity 19‐item Index.Caregiver confidence and training needs were assessed using a bespoke self‐report questionnaire assessing confidence and perceived training needs in relation to different personal care activities. Two scores were calculated separately, with higher scores indicating more confidence or higher training needs.Caregiver management style was assessed using the 28‐item caregiver self‐report Dementia Management Strategies Scale2.5Analysis was conducted in Stata17.2.5.1t‐tests with refusals of care and dividing the mean difference by the overall SD of the difference.Mean and standard deviation (SD) were calculated for continuous and normally distributed variables, and median and interquartile range (IQR) for continuous but skewed data, and frequency and percentage for categorical variables. Effect sizes were calculated for both caregiver type and caregiver training (our main exposures of interest) by running separate 2.5.2p‐values for the regression coefficients higher than 25% (p > 0.25) were not considered to be potentially important predictors of refusal of care and were not included in the multivariable model.Mixed effects linear models were used for investigating the factors associated with refusals of care. The models included a random intercept for care setting to account for the variation between care settings and any potential intra‐cluster correlation between participants from the same care setting (nested data).p < 0.25 in the univariable models, were included together in a multivariable mixed effects linear regression model. Subsequently, independent variables showing very weak associations (p ≥ 0.90) in the multivariable model were excluded, and the final model re‐estimated.The remaining predictor variables, those with The final multivariable model was used for regression diagnostics and model checking. The distribution of random effects and overall residuals were examined via Q‐Q plot and boxplot for assessing normality. Variance inflation factors were examined to check for multicollinearity.33.1Table 3.2p > 0.25), so these variables were excluded . However, these variables were directly linked to our hypotheses of interest so were retained in the final model.Screening via univariate linear mixed models suggested that dementia sub‐type, gender, ethnicity, and caregiver management may not be important predictors of refusals of care , so these were removed from the final model.An initial multivariable model was fitted . Higher levels of agitation were associated with more refusal behaviours . No associations were found between refusals of care and age of the person with dementia, caregiver support needs, psychotropic medication use, comorbidities, modifications to the bathroom or bedroom environment, professional input within the last 3 months, or neuropsychiatric symptoms as assessed by the NPI. The differences in refusals between caregiver type (care home or family) (Cohen's d = 0.068) or between caregivers with or without dementia training (d = 0.086) were small and the effect sizes do not appear to be clinically meaningful. A visual representation of the adjusted coefficients and the associated 95% confidence intervals is given in Figure Table Variance inflation factors for variables in the final model were checked for multicollinearity and were all <5, ranging between 2.21 for care setting and 1.06 for professional input in the last 3 months (mean 1.51), showing no obvious concern about collinearity , behaviours such as depression and aggression, and sleep and eating disorders in one questionnaire,Although our analysis identified an association between agitation and refusals of care in advanced dementia, the underlying causes of that agitation are varied and not always avoidable. For instance, the person may have been in pain or have had unmet needs; it is also likely that agitation was a result of the severity of the dementia itself.Often, refusals of care have been conflated with other behavioural expressions such as agitation or aggression in dementia, for example, in assessment scales of behavioural change.That independence with ADLs was associated with less refusal of care behaviours may indicate that refusals increase as dementia becomes more advanced. Or that as impairment increases, a lack of control and ability to conduct care activities in the ways in which the person with dementia could understand or would want them to be conducted leads to refusals. Feelings of dependence may contribute to the person with dementia becoming frustrated leading to refusals. Additionally, increased assistance required with ADLs, equates to more care interactions with caregivers, which would increase the assistance time in which a person may refuse assistance. Caregivers' actions can influence refusals4.1This study provides insight into the factors associated with refusals of care in advanced dementia, indicating targets for intervention as part of their prevention and management. Limitations include being reliant on subjective informant reported measures of refusals of care, having less data from care‐home settings in comparison to family settings. We used the CMAI and NPI total scores in our analysis and have not assessed individual or grouped behaviours/domains, where differences may have been found. Although we assessed multiple factors, we did not assess pain or delirium, which may have been relevant factors associated with refusals. We also did not examine care interactions, which could be one way to provide insightful information about factors associated with refusals of care. Future research should work to develop suitable interventions to reduce agitation and optimise as much independence with ADLs as possible in advanced dementia. Additionally, examining other possible factors  related to refusals of care in statistical models would improve knowledge.5Agitation and dependence in ADLs were associated with refusals of care in advanced dementia. Importantly, there were no associations with care setting (family or care home) or caregiver dementia training (yes or no) and refusals of care, indicating that refusals of care have similar prevalence regardless of caregiver status. Additionally, there are possible implications for the effects of dementia training as an intervention to prevent or reduce refusals of care. It may be that current dementia training does not cover aspects that would influence the occurrence of refusals of care, that dementia training is not effectively delivered, or that training is not put into practice. Future research should determine key components to reduce refusals, including exploring the value of reducing agitation and maximising independence.The authors have no conflict of interest to declare.Supporting Information S1Click here for additional data file.


Habitat fragmentation and isolation threaten the survival of several wide‐ranging species, such as tigers, through increased risk from diseases, disasters, climate change, and genetic depression. Identification of the habitat most likely to achieve connectivity among protected areas is vital for the long‐term persistence of tigers. We aimed to improve the mapping of potential transfrontier protected area corridors for tigers by connecting sites within the Terai Arc Landscape in Nepal and to those in India, highlighting targeted conservation actions needed along these corridors to maintain long‐term connectivity. We used least‐cost corridor modeling and circuit theory to identify potential corridors and bottlenecks in the study area. The landscape's resistance to tigers' movement was gathered from expert opinions to inform corridor modeling. We identified nine potential tiger corridors in the Terai Arc Landscape—Nepal that aligned strongly with the remaining intact habitats of the Siwalik landscape, which could facilitate tiger movement. Banke‐Bardia and Chitwan‐Parsa‐Valimiki complexes and Lagga‐Bhagga and Khata corridors were identified as high‐priority conservation cores and corridors. While our model exhibited congruence with most established corridors in the landscape, it has identified the need to enhance existing corridors to improve landscape connectivity. Several pinch points posing an increased risk to connectivity were identified. Most of these were located near the protected area boundaries and along the Nepal–India border. The Siwalik landscape holds the key to long‐term connectivity in the study area; however, immediate conservation attention is needed, particularly at pinch points, to secure this connectivity for tigers. Validation of identified corridors through empirical research and their conservation is a priority. Identification of the habitat most likely to achieve connectivity among protected areas is vital for the long‐term persistence of tigers. We used least‐cost corridor modeling and circuit theory to identify potential tiger corridors and bottlenecks in the Terai Arc Landscape in Nepal. The Siwalik hills in the study area holds the key to potential connectivity among protected areas; however, immediate conservation attention is needed, particularly at pinchpoints, to secure this connectivity for tigers. Although Nepal has five designated tiger‐bearing PAs, they form three distinct tiger subpopulations, with 169 tigers estimated in Chitwan and Parsa NPs, 150 in Banke and Bardia NPs, and 36 tigers estimated in Shukla Phanta NP  and the National Trust for Nature Conservation geoportal . Boundaries of Suhelwa WLS, Valmiki, and Pilibhit TRs were digitized from a georeferenced boundaries image file from the ENVIS Centre on Wildlife & Protected Areas database hosted by the Wildlife Institute of India (http://www.wiienvis.nic.in). PAs that shared common boundaries were considered a single core area for corridor mapping.Vector shapefiles of PAs in the study area were downloaded from the World Database on PAs (https://earthexplorer.usgs.gov). This dataset was used to generate a slope layer for the study area using the slope tool in ArcGIS.A landcover layer was created by performing multi‐spectral classification using publicly available Landsat 8 Operational Land Imager (OLI) satellite imagery at 30 m resolution to produce thematic maps identifying the following broad a priori landcover classes: forest, water bodies, agriculture, barren areas, and urban areas. Details on the landcover classification and accuracy assessment are provided in the supplementary file . ASTER‐dhttp://download.geofabrik.de). The data were processed to include only major road classes, such as highways (roads classified as trunks and with names including highways) and other roads , which were then converted into a raster grid for corridor analysis.A road network layer for our study area was generated using data downloaded from OpenStreetMap (OSM) in ESRI‐compatible shapefile format  for Nepal and Tehsils in India. The projected national population for 2021 based on Nepalese census data 2011 was used to extrapolate the population for each VDC using the ratio method CBS, . The rathttps://censusindia.gov.in).In the case of India, we used the same method to get the projected population data for 2021 at the sub‐district level from the projected population of the respective state for 2021 based on the Indian national census data 2011 (2.3.22), medium (500–1500 person/km2), high (>1500 person/km2), or absent. Roads were classified as highways (major roads), other roads (minor roads), or absence. The slope was classified into six categories, from a flat surface (0–2°) to a very steep slope (>35°)  Table . We cond°) Table .2.4We compared resistance surfaces derived from different spatial scales and weighting scenarios of the input data layers to assess the sensitivity and identify the most optimal spatial scale and layer‐weighting scenario, which were used for mapping the corridor in the landscape Figures  and S2. The CWD:EucD ratio measures the relative length of the corridor compared with the shortest possible distance between target core habitats . An ideal corridor will have a CWD:EucD ratio of 1, whereas a higher value indicates the greater difficulty or cost of movement between PAs. The CWD:LCP ratio assesses the corridor quality by measuring the average resistance encountered by tigers per unit distance along a single optimal path between PAs. The Least Cost Path (LCP) represents the path with the lowest cumulative cost of movement between two habitat fragments. Effective Resistance (Effres), calculated in the Linkage Mapper using circuit theory  using Conefor v2.6  and the probability of dispersal between habitat patches and is frequently used for prioritizing habitat cores and corridors  among the PA pairs was used to get distance thresholds in CWD . We used the linkage removal option available in the Conefor, which iteratively removes one linkage at a time to measure its impact on the total connectivity across the landscape to ascertain its importance  for their contribution to maintaining connectivity.Conefor takes two files as input; a node file representing habitat patches with associated attributes and connection files representing the link between each pair of habitat patches  and the shortest distance between Shukla Phanta NP and Pilibhit TR (6.37 km).The total area of the landscape included in this study was 66,653 km3.1Corridor models based on varying spatial scales of input data and layer‐weighting scenarios produced slightly different cost‐weighted distances and least‐cost paths. However, the least‐cost corridors between target PAs had spatial overlap across all models. We identified corridors using a 1 km spatial resolution of input data layers and layer‐weighting scenarios where the landcover and human population density layer had twice as much weight as roads and slope layers to be optimal for our analysis Figures  and S2.3.2Our final corridor dataset contained nine corridors connecting tiger‐bearing PAs within Nepal and adjacent PAs in India Table . Most ofComparatively, the difficulty of movement for tigers moving through corridors connecting Shukla Phanta NP to other PAs was greater than in corridors connecting the Chitwan‐Parsa‐Valmiki complex and the Banke‐Bardia complex to other PAs. For example, despite having a nearly similar Euclidean distance between Shukla Phanta and Dudhwa NPs and the Banke‐Bardia complex and Suhelwa WLS , the cost of movement through the corridor connecting Shukla Phanta and Dudhwa NPs was much higher than the latter Table . SimilarThe CWD:Effres, which measures the robustness of the corridor to being severed, was highest for the corridor connecting the Banke‐Bardia complex to Suhelwa WLS, indicating the presence of multiple low‐cost alternative routes, a wider corridor habitat and more robust connectivity potential between these PAs. Whereas the ratio was lowest for the corridor connecting Banke‐Bardia complex to Katerniaghat WLS, indicating fewer alternative routes available to tigers, a narrow corridor habitat and a higher risk of severing the connectivity. Across all the identified corridors, the ratio was higher for the corridors passing through the Siwalik landscape, indicating that these corridors consist of more low‐resistance alternative paths for tigers to move between PAs and, consequently, are less likely to be severed.The corridors modeled for this current study overlapped with the already established corridors in the landscape to varying degrees. While optimal corridors intersected with established corridors in several locations, a significant area outside the boundaries of existing corridors was identified as potential corridor habitat. Most of the optimal corridor habitat between Nandhaur WLS and Shukla Phanta NP was identified north of the existing Boom‐Brahmadev corridor. Similarly, most of the optimal corridor habitat between Katerniaghat WLS and Bardia NP was identified west of Geruwa River outside the Khata corridor. The corridor models also partially identified the Laljhadi‐Mohana and Basanta corridors, allowing opportunities to optimize existing corridors to improve connectivity in the landscape. However, the corridor model completely missed the Kamdi corridor established to connect Banke NP in Nepal to Suhelwa WLS in India. However, an alternative, shorter, least‐cost path was identified between these two transboundary PAs Figure .3.3market) within the Siwalik landscape which may threaten the connectivity between these two important tiger recovery sites. Pinch points near major settlements and roads intersecting the corridor were also observed for other corridors identified in the landscape . The CWD cutoff width of 20 km and 50 km produced very constricted corridors, whereas the CWD cutoff width of 200 km produced very wide and unrealistic corridors. We, therefore, present pinch points identified using a CWD cutoff width of 100 km. For the corridor connecting each pair of PAs, we identified several sections where the current flow was the highest, indicating higher resistance to movement for tigers, that is, pinch points or bottlenecks. Pinch points were mostly located in the periphery of the protected areas, where major highways intersected the corridor and along the Nepal–India border. Pinch points identified along the corridor connecting the Banke‐Bardia complex to Katarniaghat WLS and Shukla Phanta NP to Dudhwa NP could jeopardize future transboundary connectivity. Pinch points near PAs were particularly evident for corridors connecting Shukla Phanta NP to other PAs , followed by the Banke‐Bardia complex  (S4). The contribution of protected areas within TAL‐India, except for Pilibhit TR, varied depending upon the selection of PA attribute for analysis (Table Banke‐Bardia complex was the most important PA in the landscape based on its contribution to habitat availability and maintaining tiger connectivity compared to other PAs. Despite its relatively smaller size, Shukla Phanta NP was more important for maintaining landscape connectivity based on the highest The Lagga Bhagga corridor connecting the Shukla Phanta NP to Pilibhit TR was identified as the highest‐priority linkage in terms of its contribution to maintaining landscape connectivity across both scenarios where the PAs' size and estimated tiger population were considered. The Khata corridor connecting the Banke‐Bardia complex to Katerniaghat WLS ranked second. Removing the linkages between the Chitwan‐Parsa‐Valmiki complex and the Banke‐Bardia complex and between the Bardia‐Bardia complex and Shukla NP did not affect the overall landscape connectivity Table .4We identified potential corridors connecting tiger‐bearing PAs in Nepal and India in the Terai Arc Landscape, one of the most important tiger conservation landscapes, by completing a landscape‐level resistance mapping analysis informed by expert knowledge. Given the dynamic landscape and ongoing threats to connectivity (Kanagaraj et al., Short‐distance corridors are generally expected to provide better connectivity than longer corridors Haddad,  due to tThe Chitwan‐Parsa‐Valmiki complex and the Banke‐Bardia complex, supporting the largest population of tigers and contiguous tiger habitat in the landscape, were most important for maintaining connectivity for tigers. In the most comprehensive global assessment of tiger landscapes, these two sites were also identified as the Level 2 priority conservation landscape for tigers, with sufficient interconnected habitats to support a breeding population of more than 50 tigers (Sanderson et al., Our analysis has revealed that removing corridors among the Chitwan‐Parsa‐Valimki complex, the Banke‐Bardia complex and Shukla Phanta NP did not affect the connectivity across the landscape. This is likely because the cost of directly moving among these PAs is greater for tigers than through other PAs that serve as stepping stones. For example, Suhelwa WLS, is a potential stepping stone for tigers moving from the Chitwan‐Parsa‐Valmiki complex to the Banke‐Bardia complex. Similarly, Katarniaghat WLS and Dudhwa NP are likely stepping stones for tigers moving from the Banke‐Bardia complex to Shukla Phanta NP. Improving the quality of the corridor habitat could reduce the cost of movement for tigers among the three most important core habitats for tigers in the landscape. Conservation prioritization will likely benefit the Suhelwa WLS, which currently does not support any tigers, to accommodate the tigers arriving from the landscape's two highest‐priority tiger core habitats. The prioritization of the cores and corridors presented in this paper should not be considered in isolation but in conjunction with other conservation prioritization tools.We identified some overlap between modeled least‐cost corridors and existing corridors in the landscape but also found some potential for further optimization. For example, our analysis identified a corridor overlapping a portion of the Khata corridor with additional potential corridor habitat situated west of the Geruwa River. Previous studies also suggested that restoring 0.5 km of habitat on either side of the Khata corridor improved connectivity (Kanagaraj et al., While there is a huge potential for improving connectivity, we identified several pinch points in the landscape that, when left unaddressed, pose a threat to connectivity. Most of the pinch points were identified on the periphery of the PAs along existing transboundary corridors and where roads intersected the corridors, likely due to the high density of settlements around PAs of the TAL‐Nepal (Chanchani et al., Pinch points introduced by road networks also pose a significant risk to connectivity for our landscape as also reported previously elsewhere (Hilty et al., The majority of the corridors were identified through Siwalik, which is key to maintaining connectivity for the tiger in the landscape. Because of the intact forest habitat, corridors identified through the Siwalik landscapes were wider, less resistant and less likely to be severed than corridors in the lowland. Wider corridors provide more alternative routes for species movement, and even if one route is severed, species can use other alternatives, making it less susceptible to being severed. Our finding is consistent with previous studies reporting on the importance of Siwalik hills in connecting the tiger population of the TAL‐Nepal (Kanagaraj et al., As with any other ecological model, our analysis is subject to errors resulting from untested assumptions of the connectivity model, uncertainties associated with the habitat selection by species during movement and dispersal, and the accuracy of spatial data layers in representing actual landscape conditions. Assessment of tiger corridors in the landscape through other available methods such as resistant kernel density, circuitscape, factorial least‐cost path and based on data sourced from genetic, telemetry, and species distribution studies would be useful to improve corridor identification further. Nonetheless, we anticipate that the corridors identified in our analysis will be useful for policymakers, conservation practitioners, and researchers in prioritizing connectivity conservation initiatives in the Siwalik landscape and informing future research and planning to secure landscape connectivity in the study area.5Securing connectivity for the tiger has been recognized as a major conservation action needed to ensure the species' long‐term survival DNPWC, . Our conThe corridors identified in our study have implications for local, national, and global tiger conservation efforts and government obligations toward the Convention of Biological Diversity, sustainable development goals, and several other conservation and climate change frameworks to which the government is a party. Conservation of these potential corridors identified between PAs of Nepal through increased protection status, habitat restoration, limiting impacts of infrastructure development, and habitat encroachment and resource exploitation will help the government of Nepal to achieve the national targets for tiger and protected area conservation DNPWC, , 2022 anTek Bhatt: Conceptualization‐Lead, Formal analysis‐Lead, Methodology‐Lead, Writing – original draft‐Lead, Writing – review & editing‐Equal. Guy Castley: Conceptualization‐Equal, Formal analysis‐Equal, Supervision‐Equal, Writing – review & editing‐Equal. Rebecca Sims‐Castley: Data curation‐Equal, Formal analysis‐Equal, Methodology‐Supporting, Software‐Supporting, Writing – review & editing‐Equal. Hem Baral: Conceptualization‐Equal, Formal analysis‐Equal, Supervision‐Equal, Writing – review & editing‐Equal. Ali Chauvenet: Conceptualization‐Equal, Formal analysis‐Equal, Supervision‐Equal, Writing – review & editing‐Equal.Not Applicable.The authors declare that they have no competing interests.Data S1: Supporting InformationClick here for additional data file.


The average number of these risk factors for not starting treatment per patient increased over time (R2 = 0.66 p < .001). Independent of these, there was an additional 5% reduction in rate of treatment initiation in each successive year of the programme . In conclusion, disengagement from care before treatment uptake was found to be a growing threat to elimination. Despite provision of community‐based test‐to‐cure pathways, there are persistent barriers to treatment uptake and these are increasing over time.Most high‐income countries are not on track to achieve the World Health Organization hepatitis C elimination targets. As elimination programmes assess growing proportions of patients in community‐based pathways, rates of treatment uptake may fall. We aimed to identify factors associated with DAA treatment uptake and measure changes in their prevalence over time. We performed a time‐to‐treatment analysis on 2728 patients approved for hepatitis C Direct‐Acting Antiviral treatment in the North Central London region between January 2016 and October 2019. We investigated the association between treatment uptake and factors including assessment/treatment setting , patient age, gender, injection drug use, harmful alcohol use, cirrhosis status and previous treatment. The likelihood of treatment uptake was reduced by three independent risk factors. These included assessment setting: prison‐based or drug‐service pathways (aHR 0.29 or 0.81 vs. hospital outpatient pathway, 95% CI 0.21–0.40 and 0.70–0.94 respectively,  DAAdirect‐acting antiviralHCVhepatitis C virusIDUinjection drug useMDTmultidisciplinary teamNCLnorth central LondonODNoperational delivery networkPMSpatient management systemPWIDpeople who inject drugsWHOWorld Health Organization1The World Health Organization (WHO) has set a goal for the elimination of hepatitis C as a public health threat by 2030, defined as an 90% reduction in incidence and 65% reduction in hepatitis C‐attributable death.Dynamic mathematical transmission modelling using global data from 2015 to 2016 DAA elimination programmesDAA treatment uptake rates are falling in high income countries and 76% of these are not on track to achieve elimination targets, according to updated analyses.Patient groups with high rates of disengagement between treatment approval and initiation are likely to account for an increasing proportion of untreated cohorts as elimination programmes move from hospital to community‐based pathways. Even if total numbers of patients entering the care cascade are increased by case‐finding initiatives, it is unclear whether treatment uptake rates can be sustained at sufficient levels for elimination. Additionally, current modelling estimates do not account for COVID‐19‐related disruptions in HCV care,We aimed to identify factors associated with treatment uptake and investigate whether the risk factors for not starting treatment were becoming more prevalent over time. We also aimed to determine whether rates of treatment uptake after approval are changing as the hepatitis C elimination programme progresses in North Central London.2We analysed a cohort of 2728 patients assessed and approved for DAA treatment in the North Central London (NCL) hepatitis C operational delivery network (ODN) between January 2016 and October 2019. In addition to 8 partner hospital sites, the NCL ODN delivers embedded community‐only hepatitis C diagnosis‐to‐cure pathways in 14 drug and alcohol services and two prisons, one of which is a large remand prison with a turnover of approximately 300 inmates per month. In each community service, a clinical nurse specialist provides assessment , treatment counselling and initiation, treatment monitoring and outcome testing, such that the patient does not have to visit services outside the one with which they are already engaged. Consultations are aligned to opioid substitution therapy supervision in drug and alcohol services and hospital investigations are only required in those with cirrhosis who require surveillance for liver cancer and/or varices. The ODN also includes two large HIV services in which hepatitis C treatment is aligned to HIV care.Data were routinely prospectively collected in all patients through a bespoke patient management system (PMS) which time‐stamps progress through stages of the care cascade and pathway processes. This permits measurement of duration of “system‐only” stages, such as drug–drug interaction checking, application for high‐cost drug approval, prescribing, dispensing and couriering treatment courses to community‐based centres. NHS England mandated a clinical prioritization scheme until 2018The primary outcome was initiation of hepatitis C treatment and a time‐to‐treatment analysis was performed. The sample size was constrained by available data but it was adequate to allow detection of a hazard ratio of 0.84 for factors that occur in at least 10% of study participants (80% power and 5% Type I error). Patient‐related variables in the model included age, gender, a history of intravenous drug use (IDU), born in the UK or elsewhere, interferon treatment experience, hepatocellular carcinoma, a significant alcohol history felt to be contributing to liver disease, liver transplantation, need for renal dialysis, HIV status, viral HCV genotype and liver disease stage. Pathway‐related factors included assessment and treatment setting  and when in the DAA programme the patient was referred for treatment .Previous studies investigating treatment uptake rates in the DAA era have used a multivariable logistic regression analysis to identify factors associated with this outcome.To evaluate the impact of co‐existent factors which negatively impact on likelihood of treatment uptake, we performed a secondary time‐to‐treatment analysis considering the number of risk factors for not starting treatment that an individual had.Elimination programmes will accumulate patients whose progression from approval to treatment is delayed, such that the average duration of delay will inevitably increase. This confounds estimates of whether delays between approval and treatment are increasing as the elimination programme continues. We therefore performed a correlation analysis between the month of assessment (from beginning of the programme) and the mean number of risk factors associated with not starting treatment in all patients presenting in that month. The dependent variable (mean number of risk factors) was normally distributed so a Pearson's correlation coefficient was derived.To investigate the impact of delays between treatment approval and initiation on healthcare team workload, data were also collected on the number of contacts made with patients by pathway navigators and nurse specialists between the treatment approval and start dates. A correlation analysis was performed between approval‐to‐treatment time and number of healthcare contacts recorded, deriving a Spearman's rank correlation coefficient due to the non‐parametric distribution of the dependent variable (number of contacts).Ethical approval was obtained from the Health Research Authority (REC reference 21/HRA/0929). Informed consent was not required to analyse routinely collected pseudonymized data. All analyses were performed in SPPS version 26 (IBM corporation).33.1The baseline characteristics of the patient cohort are shown in Table 2442 patients (90%) commenced treatment between January 2016 and October 2019 and the median time from approval to starting treatment or censor was 51 days (range 0–1509). Delays between MDT approval and treatment which were attributable to system‐only stages in the pathway  across all treatment settings (data available in 1611 cases) were on average 3.7 days duration (95% CI 3.3–4.2), representing only 8% of the median time between MDT approval and treatment in this group.3.2Variables associated with the likelihood of treatment initiation after approval are shown in Table p < .001). Assessment and treatment in drug and alcohol services was associated with a 19% lower likelihood of commencing treatment, compared with hospital , despite the provision of in‐house hepatitis C assessment and treatment monitoring aligned to opioid substitution therapy. A history of IDU was only associated with a reduced likelihood of commencing treatment in unadjusted analysis and became non‐significant in adjusted analysis, suggesting a correlation and more meaningful effect of drug‐service setting than IDU. However, a determination by the referring clinician that alcohol was a significant contributor to liver disease was independently associated with lower likelihood of starting treatment in the adjusted model . This association became non‐significant when prisons‐based pathway settings were excluded from analysis (Supporting information).The setting of the assessment and treatment pathway had the most significant impact on likelihood of treatment in the Cox regression analysis. Patients assessed in prison were 70% less likely to start treatment compared with patients assessed in hospital clinic settings . Age, gender, previous treatment, liver disease stage, hepatocellular carcinoma and liver transplantation were not independently associated with likelihood of progression to treatment, although the numbers in the analysis were low for the latter two factors.Those of UK origin were less likely to start treatment than those born outside the UK  and those infected with genotypes other than 1 or 4 , which is attributable to patients meeting clinical priority thresholds and MDT approval in advance of NHS commissioning of dialysis‐compatible and genotype 3 treatments, which occurred during the study interval. HIV co‐infection was a strong positive predictor of treatment uptake .There was reduced treatment uptake in patients requiring dialysis  had a 42% lower rate of treatment than those with no risk factors (n = 695) . Importantly, the Kaplan–Meier curve of this group plateaus, indicating a ceiling of treatment uptake in those with multiple risk factors for disengagement before treatment uptake.Renal dialysis and genotype were not included because the prolonged duration between approval and treatment were attributable to historical changes in treatment availability, as previously described. The month of referral into programme was also excluded as a time‐dependent variable which would confound the trajectory of progress to treatment in the group over time. Increasing numbers of any of these three risk factors decreased the likelihood of starting treatment Figure . Those wR2 = 0.66, p < .0001). Assessment in pathways embedded in drug and alcohol services is increasing in the NCL ODN region , as is the proportion of those with a history of IDU  and the proportion of patients in whom alcohol is a significant contributor to liver disease .Duration of time between approval and treatment increased as the programme progressed (Supporting information) and this may be related to changes over time in the risk factor profile of patients. However, this is affected by lead‐time bias since those treated more recently had a longer potential interval from approval. We therefore examined whether the three independent risk factors for not starting treatment outlined above were becoming more prevalent. Figure 3.4R = 0.6, p < .0001).We examined the relationship between the number of patient contacts made by NCL ODN staff  and the time between MDT approval and treatment initiation , independently of these risk factors. Not being engaged with hepatitis C treatment increases the risks of onward transmission, individual harm and healthcare workload and is a growing threat to hepatitis C elimination.Enhancing case‐finding and treatment uptake are both essential for achieving HCV elimination. Whilst diagnosis rates are relatively easy to measure, determining whether delays between stages in the care cascade are increasing is hampered by study interval biases and the lack of national‐level data encompassing accurately time‐stamped progress through the care cascade. We have analysed a cohort in which these data were available and have identified two separate phenomena which indicate that patient disengagement before treatment uptake is increasing as our regional elimination programme continues. The first is that there are several independent risk factors for disengagement and their prevalence in individual patients is rising as the DAA programme progresses. The second phenomenon is that the likelihood of starting treatment is reducing over time, independently of these risk factors and their growing prevalence. One explanation for this may be the “warehouse effect”.Together, these undermine the key assumption made in models of trajectories towards elimination that treatment uptake rates at the beginning of elimination programmes will be maintained.Some of the factors impacting treatment uptake identified herein have been reported previously. Difficulties in initiating treatment in prison settings have been recognized in the literature.People who inject drugs experience many barriers to hepatitis C treatment,Harmful alcohol use (as determined by assessing clinician) was associated with reduced treatment uptake in NCL and alcohol use disorders have been identified in the literature as a barrier to DAA treatment uptake in cohort studies in CanadaThe finding that those born outside the UK were more likely to start DAA treatment may be explained by our analysis not adjusting for differences in socioeconomic status  of the study population died without treatment, which would not impact significantly upon the analysis. The lack of socioeconomic data (or complete postcode data from which this can be derived) means this important factor has been omitted from our model. We have also used a crude surrogate of healthcare workload in number of patient contacts by NCL ODN staff before treatment, which does not capture the efforts of peer support workers and community services to engage patients. The generalizability of the results is reduced by region‐specific factors, such as having a large remand (rather than long‐stay) prison population; however, the baseline patient characteristics of this cohort are typical of populations with hepatitis C in high‐income countries.Further qualitative investigation is needed to explore influences on patient engagement with the hepatitis C care cascade in the UK in the DAA era, such as the effects of mental health and socioeconomic status. In future, these risk factors could be combined with dynamic real‐time data on patient interaction with one stage of the pathway, such that disengagement from a subsequent stage can be pre‐empted with supportive interventions. It will also be important to evaluate the impact of these factors on testing and treatment uptake in the post‐COVID‐19 pandemic era, as disruption to health and social care services is likely to have aggravated existing barriers to care.In conclusion, disengagement from care between treatment approval and initiation was found to be a substantial and growing threat to hepatitis C elimination in London. The identified risk factors for disengagement before treatment uptake are increasing in prevalence and a combination of these significantly reduces the likelihood of treatment initiation. There is an additional independent reduction in treatment uptake with each year of the elimination programme, despite the provision of community‐based pathways. This analysis is of value to those deciding how to distribute resources between stages in the hepatitis care cascade to accelerate progress to elimination and also for targeting support for treatment uptake towards those most in need.DM developed the concept for the study and built the patient management system from which data were acquired. DM, KB, CS and AR were involved in designing the study. DM and KB acquired, analysed and interpreted the data with statistical supervision by CS. KB drafted and DM, CS and AR revised the manuscript. All authors read and approved the final manuscript.No external financial support was received for the conduct of the research or preparation of the article.Dr Smith reports grants from ViiV Healthcare and personal fees from Gilead Sciences Ltd, outside the submitted work. The other authors declare no competing interests.Data S1Click here for additional data file.