Cancer Loyalty Card Study (CLOCS): protocol for an observational case-control study focusing on the patient interval in ovarian cancer diagnosis

Overcoming biases of individual level shopping history data in health research

Novel sources of population data, especially administrative and medical records, as well as the digital footprints generated through interactions with online services, present a considerable opportunity for advancing health research and policymaking. An illustrative example is shopping history records that can illuminate aspects of population health by scrutinizing extensive sets of everyday choices made in the real world. However, like any dataset, these sources possess specific limitations, including sampling biases, validity issues, and measurement errors. To enhance the applicability and potential of shopping data in health research, we advocate for the integration of individual-level shopping data with external datasets containing rich repositories of longitudinal population cohort studies. This strategic approach holds the promise of devising innovative methodologies to address inherent data limitations and biases. By meticulously documenting biases, establishing validated associations, and discerning patterns within these amalgamated records, researchers can extrapolate their findings to encompass population-wide datasets derived from national supermarket chain. The validation and linkage of population health data with real-world choices pertaining to food, beverages, and over-the-counter medications, such as pain relief, present a significant opportunity to comprehend the impact of these choices and behavioural patterns associated with them on public health.

Using online search activity for earlier detection of gynaecological malignancy

BACKGROUND

Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses.

METHODS

This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235.

RESULTS

The cohort had a median age of 53 years old (range 20-81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral.

CONCLUSIONS

Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes.

Impact of pension income on healthcare utilization of older adults in rural China

OBJECTIVE

In China, rural residents experience poorer health conditions and a higher disease burden compared to urban residents but have lower healthcare services utilization. Rather than an insurance focus on enhanced healthcare services utilization, we aim to examine that whether an income shock, in the form of China's New Rural Pension Scheme (NRPS), will affect outpatient, inpatient and discretionary over-the-counter drug utilization by over 60-year-old rural NRPS residents.

METHODS

Providing a monthly pension of around RMB88 (USD12.97), NRPS covered all rural residents over 60 years old. Fuzzy regression discontinuity design (FRDD) was employed to explore the NRPS causal effect on healthcare services utilization, measured by outpatient and inpatient visits and discretionary over-the-counter drug purchases. The nationwide China Health and Retirement Longitudinal Study (CHARLS) 2018 provided the data.

RESULTS

Without significant changes in health status and medication needs, 60-plus-year-old NRPS recipients significantly increased the probability of discretionary OTC drug purchases by 33 percentage points. NRPS had no significant effect on the utilization of outpatient and inpatient utilization. The increase in the probability of discretionary OTC drug purchases from the NRPS income shock was concentrated in healthier and low-income rural residents. Robustness tests confirmed that FRDD was a robust estimation method and our results are robust.

CONCLUSION

NRPS was an exogenous income shock that significantly increased the probability of discretionary over-the-counter drug purchases among over 60-year-old rural residents, but not the utilization of inpatient or outpatient healthcare services. Income remains an important constraint for rural residents to improve their health. We recommend policymakers consider including commonly used over-the-counter drugs in basic health insurance reimbursements for rural residents; provide health advice for rural residents to make discretionary over-the-counter drug purchases; and to mount an information campaign on over-the-counter drug purchasing in order to increase the health awareness of rural residents.

Cancer Loyalty Card Study (CLOCS): feasibility outcomes for an observational case-control study focusing on the patient interval in ovarian cancer

OBJECTIVES

Ovarian cancer symptoms are often non-specific and can be normalised before patients seek medical help. The Cancer Loyalty Card Study investigated self-management behaviours of patients with ovarian cancer prior to their diagnosis using loyalty card data collected by two UK-based high street retailers. Here, we discuss the feasibility outcomes for this novel research.

DESIGN

Observational case-control study.

SETTING

Control participants were invited to the study using social media and other sources from the general public. Once consented, control participants were required to submit proof of identification (ID) for their loyalty card data to be shared. Cases were identified using unique National Health Service (NHS) numbers (a proxy for ID) and were recruited through 12 NHS tertiary care clinics.

PARTICIPANTS

Women in the UK, 18 years or older, with at least one of the participating high street retailers' loyalty cards. Those with an ovarian cancer diagnosis within 2 years of recruitment were considered cases, and those without an ovarian cancer diagnosis were considered controls.

PRIMARY OUTCOME MEASURES

Recruitment rates, demographics of participants and identification of any barriers to recruitment.

RESULTS

In total, 182 cases and 427 controls were recruited with significant differences by age, number of people in participants' households and the geographical region in the UK. However, only 37% (n=160/427) of control participants provided sufficient ID details and 81% (n=130/160) matched retailers' records. The majority of the participants provided complete responses to the 24-Item Ovarian Risk Questionnaire.

CONCLUSIONS

Our findings show that recruitment to a study aiming to understand self-care behaviours using loyalty card data is challenging but feasible. The general public were willing to share their data for health research. Barriers in data sharing mechanisms need to be addressed to maximise participant retention.

TRIAL REGISTRATION NUMBER

ISRCTN14897082, CPMS 43323, NCT03994653.

Understanding Public Attitudes and Willingness to Share Commercial Data for Health Research: Survey Study in the United Kingdom

BACKGROUND

Health research using commercial data is increasing. The evidence on public acceptability and sociodemographic characteristics of individuals willing to share commercial data for health research is scarce.

OBJECTIVE

This survey study investigates the willingness to share commercial data for health research in the United Kingdom with 3 different organizations (government, private, and academic institutions), 5 different data types (internet, shopping, wearable devices, smartphones, and social media), and 10 different invitation methods to recruit participants for research studies with a focus on sociodemographic characteristics and psychological predictors.

METHODS

We conducted a web-based survey using quota sampling based on age distribution in the United Kingdom in July 2020 (N=1534). Chi-squared tests tested differences by sociodemographic characteristics, and adjusted ordered logistic regressions tested associations with trust, perceived importance of privacy, worry about data misuse and perceived risks, and perceived benefits of data sharing. The results are shown as percentages, adjusted odds ratios, and 95% CIs.

RESULTS

Overall, 61.1% (937/1534) of participants were willing to share their data with the government and 61% (936/1534) of participants were willing to share their data with academic research institutions compared with 43.1% (661/1534) who were willing to share their data with private organizations. The willingness to share varied between specific types of data-51.8% (794/1534) for loyalty cards, 35.2% (540/1534) for internet search history, 32% (491/1534) for smartphone data, 31.8% (488/1534) for wearable device data, and 30.4% (467/1534) for social media data. Increasing age was consistently and negatively associated with all the outcomes. Trust was positively associated with willingness to share commercial data, whereas worry about data misuse and the perceived importance of privacy were negatively associated with willingness to share commercial data. The perceived risk of sharing data was positively associated with willingness to share when the participants considered all the specific data types but not with the organizations. The participants favored postal research invitations over digital research invitations.

CONCLUSIONS

This UK-based survey study shows that willingness to share commercial data for health research varies; however, researchers should focus on effectively communicating their data practices to minimize concerns about data misuse and improve public trust in data science. The results of this study can be further used as a guide to consider methods to improve recruitment strategies in health-related research and to improve response rates and participant retention.

Association Between Purchase of Over-the-Counter Medications and Ovarian Cancer Diagnosis in the Cancer Loyalty Card Study (CLOCS): Observational Case-Control Study

BACKGROUND

Over-the-counter (OTC) medications are frequently used to self-care for nonspecific ovarian cancer symptoms prior to diagnosis. Monitoring such purchases may provide an opportunity for earlier diagnosis.

OBJECTIVE

The aim of the Cancer Loyalty Card Study (CLOCS) was to investigate purchases of OTC pain and indigestion medications prior to ovarian cancer diagnosis in women with and without ovarian cancer in the United Kingdom using loyalty card data.

METHODS

An observational case-control study was performed comparing purchases of OTC pain and indigestion medications prior to diagnosis in women with (n=153) and without (n=120) ovarian cancer using loyalty card data from two UK-based high street retailers. Monthly purchases of pain and indigestion medications for cases and controls were compared using the Fisher exact test, conditional logistic regression, and receiver operating characteristic (ROC) curve analysis.

RESULTS

Pain and indigestion medication purchases were increased among cases 8 months before diagnosis, with maximum discrimination between cases and controls 8 months before diagnosis (Fisher exact odds ratio [OR] 2.9, 95% CI 2.1-4.1). An increase in indigestion medication purchases was detected up to 9 months before diagnosis (adjusted conditional logistic regression OR 1.38, 95% CI 1.04-1.83). The ROC analysis for indigestion medication purchases showed a maximum area under the curve (AUC) at 13 months before diagnosis (AUC=0.65, 95% CI 0.57-0.73), which further improved when stratified to late-stage ovarian cancer (AUC=0.68, 95% CI 0.59-0.78).

CONCLUSIONS

There is a difference in purchases of pain and indigestion medications among women with and without ovarian cancer up to 8 months before diagnosis. Facilitating earlier presentation among those who self-care for symptoms using this novel data source could improve ovarian cancer patients' options for treatment and improve survival.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03994653; https://clinicaltrials.gov/ct2/show/NCT03994653.

Testing the Effectiveness of an Animated Decision Aid to Improve Recruitment of Control Participants in a Case-Control Study: Web-Based Experiment

BACKGROUND

Participation in case-control studies is crucial in epidemiological research. The self-sampling bias, low response rate, and poor recruitment of population representative controls are often reported as limitations of case-control studies with limited strategies to improve participation. With greater use of web-based methods in health research, there is a further need to understand the effectiveness of different tools to enhance informed decision-making and willingness to take part in research.

OBJECTIVE

This study tests whether the inclusion of an animated decision aid in the recruitment page of a study website can increase participants' intentions to volunteer as controls.

METHODS

A total of 1425 women were included in a web-based experiment and randomized to one of two experimental conditions: one in which they were exposed to a simulated website that included the animation (animation; n=693, 48.6%), and one in which they were exposed to the simulated website without the animation (control; n=732, 51.4%). The simulated website was adapted from a real website for a case-control study, which invites people to consider taking part in a study that investigates differences in purchasing behaviors between women with and without ovarian cancer and share their loyalty card data collected through 2 high street retailers with the researchers. After exposure to the experimental manipulation, participants were asked to state (1) their intention to take part in the case-control study, (2) whether they would be willing to share their loyalty card for research, and (3) their willingness to be redirected to the real website after completing the survey. Data were assessed using ordinal and binary logistic regression, reported in percentages (%), adjusted odds ratio (AOR), and 95% confidence intervals.

RESULTS

Including the animation in the simulated website did not increase intentions to participate in the study (AOR 1.09; 95% CI 0.88-1.35) or willingness to visit the real study website after the survey (control 50.5% vs animation 52.6%, AOR 1.08; 95% CI 0.85-1.37). The animation, however, increased the participants' intentions to share the data from their loyalty cards for research in general (control 17.9% vs animation 26%; AOR 1.64; 95% CI 1.23-2.18).

CONCLUSIONS

While the results of this study indicate that the animated decision aid did not lead to greater intention to take part in our web-based case-control study, they show that they can be effective in increasing people's willingness to share sensitive data for health research.