Surrogate endpoints, used to substitute for and predict final clinical outcomes, are increasingly being used to support submissions to health technology assessment agencies. The increase in the use of surrogate endpoints has been accompanied by literature describing the frameworks and statistical methods to ensure their robust validation. The aim of this review was to assess how surrogate endpoints have recently been used in oncology technology appraisals by the National Institute for Health and Care Excellence (NICE) in England and Wales.

This article identifies technology appraisals in oncology published by NICE between February 2022 and May 2023. Data are extracted on the use and validation of surrogate endpoints including purpose, evidence base, and methods used.

Of the 47 technology appraisals in oncology available for review, 18 (38 percent) utilized surrogate endpoints, with 37 separate surrogate endpoints being discussed. However, the evidence supporting the validity of the surrogate relationship varied significantly across putative surrogate relationships with 11 providing randomized controlled trial evidence, 7 providing evidence from observational studies, 12 based on the clinical opinion, and 7 providing no evidence for the use of surrogate endpoints.

This review supports the assertion that surrogate endpoints are frequently used in oncology technology appraisals in England and Wales and despite the increasing availability of statistical methods and guidance on appropriate validation of surrogate endpoints, this review highlights that use and validation of surrogate endpoints can vary between technology appraisals, which can lead to uncertainty in decision making.

The COVID-19 pandemic has disproportionately affected women's mental health. However, most evidence has focused on mental illbeing outcomes, and there is little evidence on the mechanisms underlying this unequal impact.

To investigate gender differences in the long-term trajectories of life satisfaction, how these were affected during the pandemic and the role of time-use differences in explaining gender inequalities.

We used data from 6766 (56.2% women) members of the 1970 British Cohort Study (BCS70). Life satisfaction was prospectively assessed between the ages of 26 (1996) and 51 (2021) years, using a single question with responses ranging from 0 (lowest) to 10 (highest). We analysed life satisfaction trajectories with piecewise latent growth curve models, and investigated whether gender differences in the change in the life satisfaction trajectories with the pandemic were explained by self-reported time spent doing different paid and unpaid activities.

Women had consistently higher life satisfaction than men before the pandemic (Δintercept,unadjusted = 0.213, 95% CI 0.087–0.340; P = 0.001) and experienced a more accelerated decline with the pandemic onset (Δquad2,unadjusted = −0.018, 95% CI −0.026 to −0.011; P < 0.001). Time-use differences did not account for the more accelerated decrease in women's life satisfaction levels with the pandemic (Δquad2,adjusted = −0.016, 95% CI −0.031 to −0.001; P = 0.035).

Our study shows pronounced gender inequalities in the impact of the pandemic on the long-term life satisfaction trajectories of adults in their 50s, with women losing their pre-pandemic advantage over men. Self-reported time-use differences did not account for these inequalities. More research is needed to tackle gender inequalities in population mental health.

A significant rise in mental health disorders was expected during the COVID-19 pandemic. However, referrals to mental health services dropped for several months before rising to pre-pandemic levels.

To identify trajectories of incidence and risk factors for common mental disorders among the general population during 14 months of the COVID-19 pandemic, to inform potential mental health service needs.

A cohort of 33 703 adults in England in the University College London COVID-19 Social Study provided data from March 2020 to May 2021. Growth mixture modelling was used to identify trajectories based on the probability of participants reporting symptoms of depression (Patient Health Questionnaire-9) or anxiety (Generalised Anxiety Disorder-7) in the clinical range, for each month. Sociodemographic and personality-related characteristics associated with each trajectory class were explored.

Five trajectory classes were identified for depression and anxiety. Participants in the largest class (62%) were very unlikely to report clinically significant symptom levels. Other trajectories represented participants with a high likelihood of clinically significant symptoms throughout, early clinically significant symptoms that reduced over time, clinically significant symptoms that emerged as the pandemic unfolded and a moderate likelihood of clinically significant symptoms throughout. Females, younger adults, carers, those with existing mental health diagnoses, those that socialised frequently pre-pandemic and those with higher neuroticism scores were more likely to experience depression or anxiety.

Nearly 40% of participants followed trajectories indicating risk of clinically significant symptoms of depression or anxiety. The identified risk factors could inform public health interventions to target individuals at risk in future health emergencies.

Although the COVID-19 pandemic has affected depression, evidence of the role of pre-pandemic history of depression remains limited.

We investigated how long-term trajectories of depressive symptomatology before the COVID-19 pandemic were related to depression during the pandemic, over and above the latest pre-pandemic depression status. Furthermore, we examined whether those experiencing depression closer to the pandemic were at higher risk during the pandemic.

Employing data from waves 4–9 of the English Longitudinal Study of Ageing (2008–2009 to 2018–2019), we used group-based trajectory modelling on 3925 English older adults aged 50+ years to identify distinctive trajectories of elevated depressive symptoms (EDS). Fully adjusted logistic models were then used to examine the associations between trajectories and depression during the COVID-19 pandemic (June–July and November–December 2020).

We identified four classes of pre-pandemic trajectories of EDS. About 5% were classed as ‘enduring EDS’, 8% as ‘increasing EDS’, 10% as ‘decreasing EDS’ and 77% as ‘absence of EDS’. Compared with respondents with absence of EDS, those with EDS history were more likely to have depression during the COVID-19 pandemic, particularly those with enduring or increasing EDS in the previous 10 years. Moreover, the frequency of EDS was more crucial in predicting the risks of depression during the pandemic than the timing of the latest episode.

Trajectories of depressive symptomatology are an important risk factor for older adults’ mental health, particularly in the context of crisis. Older people with enduring or increasing EDS should receive particular attention from policy makers when provisioning post-pandemic well-being support.

The Autism Spectrum Quotient is a popular autism screening tool recommended for identifying potential cases of autism. However, many women with autism demonstrate a different presentation of traits to those currently captured by screening measures and assessment methods, such as the Autism Spectrum Quotient.

Different models of the Autism Spectrum Quotient have been proposed in the literature, utilising different items from the original 50-item scale. Within good-fitting models, the current study aimed to explore whether these items assess autistic traits similarly across men and women.

Seventeen Autism Spectrum Quotient models were identified from the literature. Using the responses of a large sample of adults from the UK general population (5246 women, 1830 men), confirmatory factor analysis was used to evaluate the fit of each model. Measurement invariance with respect to gender, adjusting for age, was explored in the 11 model frameworks that were found to have satisfactory fit to our data.

It emerged that only two items were gender invariant (non-biased), whereas for the remaining items, the probability of endorsement was influenced by gender. In particular, women had a higher probability of endorsing items relating to social skills and communication.

If the items of the Autism Spectrum Quotient indeed reflect autism-related traits, those items should be rephrased to ensure they do not present a gender-related bias. This is vital for ensuring more timely diagnoses and support for all people with autism.

There are numerous challenges in the recruitment and retention of the medical workforce in psychiatry. This mixed-methods study examined the role of psychiatry clinical attachments for international medical graduates (IMGs) to enhance recruitment and retention. An online survey was launched to capture views and perceptions of IMGs about clinical attachments. The quantitative and qualitative responses were analysed to elicit findings.

In total, 92 responses were received, with respondents commonly from India, Pakistan and Egypt. Respondents were mostly aged 25–34, with ≥3 years of psychiatry experience. Over 80% expressed strong interest in completing a psychiatry clinical attachment and believed it would support career progression. Qualitative data indicated that IMGs hoped to gain clinical experience and understanding of the National Health Service (NHS). They wished for a clearer, simpler process for clinical attachments.

Clinical attachment can be mutually beneficial, providing IMGs with opportunity to confidently start their psychiatry career in the UK and enhance medical recruitment in mental health services across the NHS.