Although some health technology assessment (HTA) authorities prefer that preference-based measures such as the EQ-5D are used to generate utilities [37,38,39], this study was conducted with vignette-based methodology for two reasons. First, generic instruments designed to quantify overall health status may not be sensitive to specific treatment process attributes, such as those described in the current health states (e.g., coping with diagnostic uncertainty, medical testing, perceptions of various cancer types). There is a substantial and growing body of literature suggesting that quality of life and utility may be influenced not only by health status and treatment outcomes, but also by the process of receiving care [36, 40, 41]. Estimation of ‘treatment process utilities’ is a situation when generic instruments like the EQ-5D are often not considered to be appropriate because a generic instrument that assesses overall health status may not be sensitive to specific treatment process attributes [36, 40, 41]. Therefore, treatment process utilities are typically estimated using vignette-based methodology [40]. With this method, health state vignettes can describe specific medical treatments so that the resulting utilities represent the impact of these experiences [36].

Second, the goal of this study was to estimate utilities of a broad range of false-positive pathways. For several reasons, it may not be feasible to administer questionnaires to a large enough sample of patients who are currently experiencing the false-positive diagnosis described within each health state. Generic instruments like the EQ-5D are designed to assess health status ‘today,’ and it is not possible to identify a false-positive experience at the time it is occurring because neither the patient nor any clinician knows it is a false positive until after the patient is found to be negative. In addition, several of the cancer types represented in the health states (e.g., pancreatic cancer, specific sub-types of lung cancer) are not specifically detected with currently used screening procedures. Therefore, it is not currently possible to recruit any participants experiencing these false-positive health states. Furthermore, for health states describing false positives that occur with standard screening approaches (e.g., breast cancer, colorectal cancer), a false positive cannot be identified until after the follow-up testing is complete. Therefore, a generic instrument would need to be administered to an extremely large sample in order to identify the relatively small subgroups who experience the nine types of false positives described in the current health states. Finally, because generic measures provide a utility estimate only for the day they are completed, the instrument would have to be administered repeatedly for the weeks following the screening result to capture the disutility of the full false-positive pathway. In contrast, the vignette-based approach avoids these obstacles because vignettes can be drafted based on input from clinicians and valued by members of the general population without requiring a large sample of patients, and the vignette approach allows for estimation of disutility (i.e., quality-adjusted life-year [QALY] decrement) associated with the full false-positive pathway.

Health state vignettes were developed based on published literature, cancer screening guidelines, and expert interviews. Then, the health states were refined in several iterations during a pilot study. The initial health state described a 1-year period that included a negative cancer screening. All other health states described a 1-year period that included a false-positive cancer screening that was eventually resolved following diagnostic testing.

The utility difference between otherwise identical health states with and without the false-positive screening represents the disutility of the false-positive experience. Because of the 1-year time horizon, this disutility can be considered a QALY decrement. Whereas most vignette-based studies value chronic health states that remain stable over time, the current vignettes can be considered ‘path states,’ which describe a sequence of events. Like other studies involving path states, utilities were estimated for the whole path rather than each part of the path [42,43,44,45,46]. For example, if a health state described an initial cancer screening and two follow-up tests (e.g., an MRI and a PET-CT), the associated utility would represent the entire series of events, and it is not possible to derive a separate disutility for each follow-up test.

Health states were valued in a TTO utility elicitation with a sample of general population participants in the UK. Because of the COVID-19 pandemic, face-to-face interviews were not conducted during the pilot phase (April–June 2021). However, the main valuation study was conducted via individual in-person utility interviews in November 2021. Informed consent was obtained prior to each interview, and the study protocol was approved by an institutional review board (Ethical and Independent Review Services; Study 21017-01).

A variety of time horizons (i.e., the duration of time spent in each health state) can be used in TTO valuations [47, 48]. For valuations of chronic health states, longer time horizons (e.g., 10 or 20 years) are typically used. Because this study valued path states in which the events described were relatively brief (most lasting <1 month as described in the health state text and depicted in a timeline figure at the bottom of each health state), a 1-year time horizon was used. Interviewers explained to participants that the false-positive experience described in each health state occurred for only part of the year that they would value in the TTO task, rather than the whole year. Interviewers used the following language: “Over the course of the year, you will be screened for cancer, learn that you do not have cancer, and then live the remainder of the year in good health. This is shown on the timeline at the bottom of the health state. Please note that the timeline only describes the duration of these events. These events could occur at any time during the year. For the remainder of the year, you will be in good health.”

The 1-year timeline was chosen to ensure that the TTO elicitation method would be sensitive to the impact of the brief false pathways. When estimating utilities associated with brief events, a longer timeline is typically not sensitive to the impact of these events because a brief event is unlikely to have any significant impact on preference for a 10-year period. However, a 1-year time horizon can be sensitive to these short-term differences [42, 44, 45]. The 1-year time horizon also simplifies the interpretation and use of the results, because the disutility associated with each temporary event can be applied in a CUA as a QALY decrement.

Health states were developed based on literature review, cancer screening guidelines, and input from six advisors. We focused on cancer screening and diagnostic investigations associated with lung, breast, colorectal, and pancreatic cancer. These four were selected to represent cancers with well-established screening policies, cancers requiring a range of follow-up investigative procedures, and a cancer (pancreatic) that currently has no effective screening test but represents an uncommon cancer with a poor prognosis that can be detected by MCED strategies.

The literature review included peer-reviewed literature [49,50,51,52,53,54,55,56,57,58] and official guidelines for cancer screening [59,60,61,62]. Google Scholar and PubMed were searched using general terms such as ‘cancer screening procedures’ and specific terms for each type of cancer that was described in the health states (e.g., breast cancer, pancreatic cancer). Articles were selected for review if they provided information describing screening procedures in the US or UK. Websites for cancer research and patient advocacy organizations were also reviewed for cancer screening recommendations and patient-friendly language for describing various tests in the health states [61,62,63,64,65,66,67,68,69,70].

To gather further information and refine the health state text, multiple rounds of interviews were conducted with six advisors, including five clinicians experienced in cancer screening methodologies (pulmonologist, radiologist, anesthesiologist, and two oncologists). The other advisor was an academic professor who is a member of the Adult Reference Group of the UK National Screening Committee, which advises the UK government on appropriate population cancer screening policies. The advisors reported an average of over 20 years’ experience with cancer screening, and the five clinicians reported seeing between 10 and 150 patients per month. Two advisors were in London, UK, and others were in the US (Texas, California, Utah, Virginia). In the initial interviews, the advisors were asked to describe patients’ typical experiences with cancer screening and follow-up investigations after an initial positive result. These descriptions were used to develop the first draft of the health states. In subsequent discussions, the advisors reviewed and edited health state drafts to ensure the descriptions were clear and accurate representations of typical patient experiences with false-positive screenings.

For some of the health states, the time required for follow-up investigations was perceived to be longer in the UK than the US. The differences in time required for follow-up reflected longer waiting periods to receive the tests, longer waiting periods for the tests to be analyzed, and longer periods of time before results were reported to the patient. In these situations, the opinions of the UK advisors were prioritized because the utility elicitation study was planned to be conducted in the UK. All six advisors agreed that the final draft of the health states provided clear and accurate descriptions of typical experiences with false-positive screening results.

Ten health state vignettes were drafted, each describing a temporary cancer screening event. The first health state (health state A) described a true negative result (i.e., a patient is screened for cancer and receives a negative result). The other nine described a false-positive pathway in which a patient is screened for cancer, receives a positive result, completes follow-up procedures, and is then told that no sign of cancer was detected. The procedure of the initial screening test was not provided because these health states were designed to yield utilities that may be applicable to false-positives stemming from any screening test, including currently available single-cancer screening tests (e.g., mammogram, colonoscopy) and MCED tests.

Table 1 presents a list of all health states, with details on the false-positive result, the follow-up procedures, and the number of days of uncertainty prior to learning that the initial screening result was not confirmed by follow-up investigation. These health states were designed to cover a broad range of experiences, from simple to more complex and invasive follow-up procedures, as well as shorter and longer durations of uncertainty.

The health states were presented to respondents on individual cards, each with a series of bullet point descriptions organized into categories with headings intended to help the respondents understand the content: ‘cancer screening,’ ‘screening result,’ the name of each follow-up investigation (e.g., ‘CT scan,’ ‘MRI scan,’ ‘mammogram’), and ‘resolution.’ A timeline of key events within each false-positive pathway was presented at the bottom of each health state. The final health state text is presented in the electronic supplementary material (ESM).

Participants were recruited using digital social media marketing (e.g., via Facebook, Twitter, and Google). Interested participants were screened by phone for eligibility. To be eligible for this study, participants were required to be over 18 years of age, a UK resident, able to understand the assessments as judged by the investigator, able and willing to give electronic informed consent, and able to complete the protocol requirements. Because the sample was intended to match the demographics of the UK general population, there were no eligibility criteria for specific clinical characteristics, and efforts were made to mirror the UK population with regard to gender, age, racial/ethnic background, and rate of unemployment by implementing recruitment caps on various demographic groups based on UK census information. To maintain the safety of participants and interviewers during the COVID-19 pandemic, participants in the main study (which was conducted in person) were required to provide proof of vaccination and wear a face covering.

A pilot study was conducted with 30 participants in the UK (mean [standard deviation (SD)] age: 45.8 [14.5] years; 50.0% female). A three-step approach was used: (1) participants were sent a package with paper copies of all materials required for the interview (i.e., health states, background information, and questionnaires); (2) one-on-one interviews were conducted by Microsoft Teams videoconference; (3) the principal investigator and/or project manager were available to join the interview and assist whenever requested by the interviewer.

Participants completed the virtual TTO valuation and provided feedback on the health states and procedures. The pilot study was conducted in three phases (11 participants in phase 1, eight in phase 2, and 11 in phase 3) to allow for edits to the health states and expert consultation after phases 1 and 2. Participants in all phases reported a good general understanding of the health states. The health states and procedures were edited for clarity and ease of understanding. Data from the 30 pilot study participants were not included in the main analysis sample.

The health states finalized in the pilot study were used to assess preference and elicit health state utilities in the main study. Trained interviewers conducted one-on-one in-person interviews in private offices, following a semi-structured interview guide.

Participants were first introduced to the health states. Health state A was presented first followed by the groups of false-positive health states. The four groups of false-positive health states (i.e., the B, C, D, and E health states) were presented in random order. Each group was presented as a set. For example, when presenting the three lung cancer health states in group B, all three were presented on the table simultaneously, but the three were presented in random order. The health states were not presented with the organized lettering/numbering system. Instead, health states were labeled with different letters that would not provide any indication of the organizational structure or order of severity. For example, health states B1 and B2 were labeled as T and Y. Interviewers reviewed every health state in detail with the participants, who were then given an opportunity to read the materials independently and ask questions. Participants were then asked to rank the health states from most preferable to least preferable.

After completing the ranking, participants valued the health states in a TTO task with a 1-year time horizon. TTO methods have been described extensively in previous publications [30]. For each of the health states, participants were offered a series of choices between spending a 12-month period in the health state versus spending varying amounts of time in full health. Choices were presented in a booklet with bars of varying length illustrating duration of the two choices. Time in full health varied in 1-month increments, alternating between longer and shorter periods of time in full health (i.e., 12 months, 0 months [dead], 11 months, 1 month, 10 months, 2 months…). Each health state received a utility value (u) on a scale with anchors of dead (0) and full health (1) based on the choice in which the respondent was indifferent between 12 months in the health state and x months in full health. The resulting utility estimate (u) is calculated as u = x/12.

Given the content of these health states, it was expected that few participants would perceive any of them to be worse than dead. However, when this happened, interviewers switched to the ‘lead-time’ approach, which introduces a lead period in full health. The duration of the lead period can vary but is typically equal to the amount of time spent in the health state (in this case, 1 year) [71, 72]. The combination of the conventional TTO for health states perceived to be better than dead and lead-time TTO for health states perceived to be worse than dead (often called ‘composite TTO’) has frequently been used in recent studies [73,74,75] and is currently the recommended protocol by the EuroQol group [72].

Statistical analyses were conducted with SAS version 9.4. Descriptive statistics were used to summarize demographic data, health state preferences, and utilities. Categorical variables are summarized as frequencies and percentages, while means and standard deviations are reported for continuous variables.

Because health states differed only in their descriptions of the false-positive pathways, any difference in preference and utility among the health states can be attributed entirely to these false positives. The disutility of each false positive was calculated by subtracting the utility of health state A (true negative) from each health state describing a false positive.

Paired t-tests were conducted to examine differences between utility and disutility means (e.g., utility of health state A vs utility of health state B1), and independent t-tests were used to test for subgroup differences in utilities by age (median split), gender, and employment status (employed vs not employed). Post hoc descriptive analyses were conducted to provide utilities for subgroups of patients categorized based on previous experiences with cancer screening and previous diagnosis of cancer.