To adapt the Serious Illness Conversation Guide (SICG), Ariadne Labs, Massachusetts USA, to a local Singapore version and evaluate its acceptability.

Qualitative study using semistructured interviews.

49 participants (30 patients with serious illnesses, five family caregivers and 14 healthcare providers (HCP)) recruited from three public hospitals in Singapore.

Face-to-face or virtual indepth interviews.

Guided by the Heuristic Framework and Cultural Sensitivity model, we employed a multi-stage iterative design. Starting with the original SICG, we iterated the guide following three rounds of cognitive interviews among patients followed by expert consultation (n=4) to derive a local version, subsequently reviewed by caregivers and HCP. We assessed acceptability of the SICG using traffic light colour codes—red (unacceptable), orange (needs change) and green (no change) and gathered suggestions to rephrase them. Using content analysis, we compared acceptability of questions as proportion of red, orange and green responses at each interview round and inductively derived themes reflecting views towards the guide.

The original SICG showed low acceptability, and most questions received high proportions of red responses. Negative words and phrases dampening hope, lack of comprehension due to complex framing and cultural insensitivity to prognostic discussions were key themes reflecting low acceptability. Surface and deep structural revisions that centred around positive framing with hopeful language, focusing on current values and individualising conversations (‘use if appropriate’ prompts) significantly improved the guide’s acceptability.

We derived a local Singapore SICG that aligns with the core elements of the original guide and fosters cultural sensitivity. The adapted version could be further tested in other Asian countries.

Although lung cancer remains the leading cause of cancer deaths in the US, recent advances in early detection and treatment have led to improvements in survival. However, there is a considerable risk of recurrence or second primary lung cancer (SPLC) following curative-intent treatment in patients with early-stage non-small cell lung cancer (NSCLC). Professional societies recommend routine surveillance with CT to optimise the detection of potential recurrence and SPLC at a localised stage. However, no definitive evidence demonstrates the effect of imaging surveillance on survival in patients with NSCLC. To close these research gaps, the Advancing Precision Lung Cancer Surveillance and Outcomes in Diverse Populations (PLuS2) study will leverage real-world electronic health records (EHRs) data to evaluate surveillance outcomes among patients with and without guideline-adherent surveillance. The overarching goal of the PLuS2 study is to assess the long-term effectiveness of surveillance strategies in real-world settings.

PLuS2 is an observational study designed to assemble a cohort of patients with incident pathologically confirmed stage I/II/IIIA NSCLC who have completed curative-intent therapy. Patients undergoing imaging surveillance will be followed from 2012 to 2026 by linking EHRs with tumour registry data in the OneFlorida+ Clinical Research Consortium. Data will be consolidated into a unified repository to achieve three primary aims: (1) Examine the utilisation and determinants of CT imaging surveillance by race/ethnicity and socioeconomic status, (2) Compare clinical endpoints, including recurrence, SPLCs and survival of patients who undergo semiannual versus annual CT imaging and (3) Use the observational data in conjunction with validated microsimulation models to simulate imaging surveillance outcomes within the US population. To our knowledge, this study represents the first attempt to integrate real-world data and microsimulation models to assess the long-term impact and effectiveness of imaging surveillance strategies.

This study involves human participants and was approved by the University of Florida Institutional Review Board (IRB), University of Florida IRB 01, under approval number IRB202300782. The results will be disseminated through publications and presentations at national and international conferences. Safety considerations encompass ensuring the confidentiality of patient information. All disseminated data will be de-identified and summarised.