Effectiveness and utility of a patient decision aid for chemotherapy or exclusion in cisplatin-intolerant patients with locally advanced cervical cancer (CECIL): a randomized controlled trial

Introduction

Cervical cancer is one of the major causes of cancer morbidity and mortality in women, with an annual incidence of 13.6 in 100,000 women and with 30% diagnosed at an advanced stage (1). In the Philippines, it is the second most common cancer in women, with an age-standardized annual incidence of 15.2 (2).

The standard treatment for locally advanced cervical cancer (LACC) is concurrent chemoradiation (CRT) (3). Adding chemotherapy as a radiosensitizer confers a 7.5% overall survival benefit but with an 11.5% increase in grade 3–4 toxicity (4). Cisplatin is the standard agent; carboplatin is the recommended alternative (3). In patients with relative or absolute contraindications to chemotherapy, any potential survival benefit could be lost if chemotherapy results in toxicity that leads to radiotherapy (RT) interruptions or delays. RT is the primary treatment and overall treatment time prolongation decreases local control and survival (5,6).

In the Philippines, compliance and timely treatment completion is reduced by inadequate RT facilities, the protracted treatment schedule, and prohibitive treatment costs (7). A third of cervical cancers are diagnosed in the elderly (2) and a third present with ureteral obstruction (8); compliance could be further diminished due to disease complications, treatment toxicities, and their management. Decision support interventions, such as patient decision aides (PtDAs), could improve compliance and outcomes by increasing patient knowledge and satisfaction, decreasing decisional conflict and attitudinal barriers, and enhancing patient and family engagement in the decision-making process, towards optimal resource mobilization and decision implementation planning (9-11).

We previously developed and validated a PtDA for deciding about chemotherapy or its exclusion in cisplatin-intolerant patients with locally advanced cervical cancer (CECIL) (12,13). We present this article in accordance with the CONSORT reporting checklist (available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-136/rc).

Objectives

We conducted a block-randomized clinical trial to evaluate the effectiveness, in terms of decisional conflict reduction (primary objective), and utility in preparing for decision-making (secondary objective) of the PtDA. We also investigated patient determinants to the decisional outcomes (exploratory objective).

Methods

Trial registration and publication

The trial protocol was previously registered (NCT05701735) and published (12,14).

Ethical clearance

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was reviewed and approved by the Research Ethics Committee of University of Santo Tomas Hospital (REC-2023-02-003-MD), the Institutional Review Board of Manila Doctors Hospital (MDH IRB 2023-003_II-C), and the Ethics Review Committee of the University of the East Ramon Magsaysay Memorial Medical Center Inc. Research Institute for Health Sciences (1526/E/2023/098), and informed consent was obtained from all individual participants.

Study site

The study was conducted in three private centers: the University of Santo Tomas Hospital-Benavides Cancer Institute, Manila Doctors Hospital, and Our Lady of Lourdes Hospital.

Study population and recruitment

Adult cervical cancer patients with squamous, adeno- or adenosquamous histology, International Federation of Gynecology and Obstetrics (FIGO) stage IB3, IIA2, IIB–IVA, with contraindications to cisplatin, including but not limited to hydronephrosis, renal or cardiac dysfunction, frailty, or refusal, and with grade 6 level English literacy were eligible. Patients with neuroendocrine carcinoma and other histologies, metastatic disease, other active cancers or prior cancer (except for a cancer treated curatively, in remission for ≥5 years, with low recurrence risk; adequately treated lentigo maligna or non-melanoma skin cancer without evidence of disease; or adequately treated carcinoma-in-situ without evidence of disease), prior pelvic irradiation or chemotherapy, current pregnancy, or cognitive impairment or psychological disturbance limiting study compliance were excluded.

Study intervention

The prototype for a PtDA for chemotherapy or exclusion in cisplatin-intolerant patients with locally advanced cervical cancer (CECIL) was developed according to the International Patient Decision Aid Standards (IPDAS) Collaboration consensus Model Development Process (15). It consisted of a patient survey, information summary, information check, values weighing scales, and guidance to decision-making.

The patient survey included four- and five-point Likert questions on willingness to get chemotherapy, understanding of treatment options, understanding of benefits and side effects, adequacy of support and advice for decision-making, and status of decision.

The information summary was based on the National Comprehensive Cancer Network guidelines (3), local guidelines (16), and current synthesis of evidence (17,18). It summarized information on cervical cancer and outcomes without treatment; standard treatment and other options; and comparison of options in terms of procedures, benefits and side effects, and costs.

The information check consisted of five questions regarding the key information to be gained from the information summary.

The values weighing scales consisted of five-point Likert scales on perceived health, attitude towards treatment, independence, external influence, support, and decision skills, and a multiple-choice question on decision-making preference.

The guidance to decision-making included steps on how to proceed with the decision-making considering the responses to the weighing scales and the questions arising from the material.

The development, alpha-testing (pre-clinical) and peer validation of the PtDA prototype were detailed in a previous publication (13). The revised prototype (version 4) was then beta-tested (clinical pilot-testing) on three patients and one gynecologic oncologist, who were asked to accomplish the Patient and Practitioner Versions of the Patient Decision Aid-Research Group-Ottawa-Acceptability Questionnaire (PtDA-RG-O-AQ) (19) to evaluate comprehensibility, length, information, neutrality, and overall suitability for decision-making. The responses indicated satisfactory patient and practitioner acceptability. The Steering Committee reviewed and considered all suggestions and agreed that no further revision was necessary. The details of the beta-testing are summarized in supplementary file 1 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-1.pdf). The final version of the prototype that was used for the clinical trial, is attached as supplementary file 2 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-2.pdf).

Study measures

The Decision Self-Efficacy Scale (DSES) measures self-confidence in decision-making, including shared decision-making. The scale has two versions, with three- and five-response categories. The latter was used as it has a better alpha coefficient (0.92) (20). The instrument consists of 11 items. The mean score is derived and multiplied by 25; a score of 0 means “extremely low self-efficacy” and a score of 100 means “extremely high self-efficacy”.

The Decisional Conflict Scale (DCS) measures perceptions of uncertainty with regards to the decision, modifiable factors that contribute to the uncertainty (information, clarity of personal values, support), and effective decision-making (feeling that the decision is informed, values-based, practicable, and satisfactory) (21). The instrument consists of 16 items. The scale has a good correlation to constructs of knowledge, regret, and discontinuance, test-retest correlations (>0.78), alpha coefficients (>0.78), and discrimination (effect sizes of 0.2 to 0.3). Scores lower than 25 are associated with implementation; scores exceeding 37.5, with uncertainty resulting in deferral or non-implementation.

The Preparation for Decision-making Scale (PDMS) measures patient perception of how useful a PtDA or other decision support intervention is in preparing the respondent to communicate with their health provider during a consultation and in making a health decision. The instrument consists of 10 items. It has good reliability (0.944), alpha coefficient (0.92–0.96), and discrimination (effect size 1.8) (22,23).

All the instruments were self-administered in English, the original language in which they were developed.

Study design

This was a block-randomized controlled clinical trial. Each center was randomized to the control or experimental group by blocks of three. The screening is conducted by the referring gynecologic oncologist (A.B., G.A., I.T., J Madera, G Gonzalez) who was blinded to the block assignment. The randomization and informed consent procedure was conducted by the primary investigator (W Bacorro), a radiation oncologist. All participants gave written informed consent.

In both groups, all participants were asked to accomplish the patient survey from the PtDA, and evaluate their decision self-efficacy using the DSES (20) and baseline decisional conflict using the DCS (21). For the experimental group, the participants were provided the PtDA, oriented to its use and allowed to bring the PtDA home to use it in the decision-making process whichever way they preferred. The control group was not provided any decisional support intervention outside of the standard consultation.

During the follow-up visit, usually within 3–14 days from the initial visit, all patients were asked to accomplish the patient survey from the PtDA and evaluate their post-intervention decisional conflict using the DCS. The experimental group was asked to evaluate the utility of the PtDA using the PDMS (22,23) after using the PtDA and before following up with the gynecologic oncologist. Taking the post-intervention measures before the follow-up with the gynecologic oncologist allowed us to isolate the effect of the PtDA.

Sample size calculation

Minimum sample sizes of 16 and 24 for the control and experimental groups, respectively, were required based on the following assumptions. The study was exploratory and was to be followed by bigger-scale testing, thus a bigger two-sided alpha error (0.10) and a higher power (0.90) was used to maximize the detection of the outcome (24). The sample size assumed that 50% and 90% (a 40% difference) of the control and experimental groups will have post-intervention DCS scores of <25.

Recruitment of ≥24 participants in the experimental arm would allow for a power of 0.90 to detect the outcome of utility (≥75% reporting utility; versus non-utility, ≤50% reporting utility), given a one-sided alpha error of 0.10.

Assuming an attrition rate of 10%, we targeted to recruit 18 and 27 participants into the control and experimental groups.

Statistical analysis

For baseline characteristics, frequency distributions were described for categorical variables such as marital, family and socioeconomic status, educational attainment, and disease stage. Means and standard deviations or medians, interquartile ranges, and ranges were reported for continuous variables such as age and scale scores.

For the primary objective, DCS scores <25 was interpreted as low decisional conflict. The proportions of participants having baseline and post-intervention scores of <25 for each group were reported and compared using Fisher’s exact test. A 0.40 difference in the proportion with post-intervention DCS <25 was considered a significant decisional conflict reduction. The mean post-intervention DCS and mean change in DCS (∂DCS) for each group were computed and compared using two-tailed Student’s t-test or Mann-Whitney U test, depending on normality using the Shapiro-Wilk test.

For the secondary objective, the utility of the PtDA was reported as the mean overall PDMS scores and the confidence interval. The PtDA was considered utile if ≥75% of the users reported a mean overall PDMS score of ≥3.5. For each item in the PDMS, a mean ≥3.5 and a median ≥4.0 score indicated per-item utility (25,26).

For the exploratory objective, correlations between baseline characteristics (age, education, socioeconomic status, DSES) and decisional outcomes (baseline and post-intervention DCS, ∂DCS, and PDMS) were investigated. A Pearson or Spearman correlation coefficient (r) ≥0.60 was considered significant and moderate, ≥0.80, very strong, and 1.00, perfect (27). Post-hoc analysis of covariance (ANCOVA) was performed to evaluate the effectiveness of the PtDA while controlling for the effect of any identified significant covariate; ω²=0.01 was considered a small effect, 0.06, medium, and 0.14, large (28,29). Within the experimental group, post-hoc group comparisons between those with and without residual decisional conflict were performed in terms of DSES, patient values (per the CECIL weighing scales), and perceived PtDA utility.

All analyses were performed using Jamovi version 2.23.28.0; a P value of <0.10 was considered statistically significant in all analyses.

Results

Recruitment and interim analysis

From February 20, 2023, to August 18, 2024, 18 participants were recruited, eight to the control and 10 to the experimental groups. Two patients declined to participate due to decisional preference (defers to the physician, 1) and language issues (not confident regarding English proficiency, 1); two were subsequently ineligible due to findings of metastases on further workups (1) and due to transfer to another center for reasons of logistics [supplementary file 3 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-3.pdf), CONSORT Diagram].

The study was designed to detect a 0.40 superiority margin in terms of proportion of participants with low post-intervention decisional conflict. At 40% accrual, the difference in proportions was 0.15 (control, 0.75; experimental, 0.90) due to higher than the projected proportion in the control (0.50). An interim analysis to determine futility showed that with a current z-value of −0.85, the futility index was 0.999, indicating that the study should be stopped because of little chance of achieving statistical significance (30-33). Hence the decision to close the study. The details of the futility analysis are summarized in supplementary file 4 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-4.pdf).

Study population

The baseline characteristics are summarized in Table 1. The two groups are comparable in terms of age, marital status, living setup, educational attainment, employment status, socioeconomic status and disease stage. The contraindications to chemotherapy were multiple for two participants in the control group, and for six in the experimental group.

Decisional conflict reduction

At baseline, the DSES, DCS scores and proportions with low DCS scores were not statistically significant between the two groups. Post-intervention, there was no significant difference in the proportions with low DCS (Table 2). Nevertheless, mean post-intervention DCS was statistically lower in the experimental group (mean =11.6) than the control group (mean =19.3) (P=0.07). The range in ∂DCS was wider for the experimental group (–11 to +14, versus –2 to +5).

Utility in preparation for decision-making

More than 75% of the PtDA users reported a PDMS of ≥3.5, indicating utility (Table 3). For each item, the PtDA was scored at least a mean of 3.5 and a of median 4.0, supporting its utility across all the items.

Determinants of decisional outcomes

For the entire cohort, demographic variables (age, education, socioeconomic status) did not correlate with DSES (Table 4). Only the DSES showed moderate inverse correlation with the baseline (r=−0.683, P=0.002) and post-intervention DCS (r=−0.649, P=0.003). For the control group, only the socioeconomic status showed strong inverse correlation with the ∂DCS (r=−0.785, P<0.001). For the experimental group, the DSES showed strong inverse correlation with baseline (r=−0.884, P<0.001) and post-intervention DCS (r=−0.879, P<0.001) and strong direct correlation with the PDMS scores (r=0.836, P<0.001).

ANCOVA was performed to evaluate the effect of the PtDA on post-intervention DCS while controlling for the effect of DSES as a covariate. The ω² values indicate that the DSES (0.392, P<0.01) and the PtDA (0.146, P=0.02) independently account for the variation in the post-intervention DCS, both corresponding to large effect sizes.

Discussion

Reduction in decisional conflict

This block-randomized controlled trial was designed primarily to determine whether the use of a previously validated and pilot-tested PtDA would result in a decisional conflict reduction, defined as an increase of 0.40 in the proportion with low post-intervention DCS when compared to the control group. In an interim analysis at 40% however, the proportions were not significantly different (control, 0.75; experimental, 0.90); futility analysis supported discontinuing the study due to low chances of achieving statistically significant results regarding the primary objective. We believe that this could be due to the cutoff definition for low DCS, or the definition for decisional conflict reduction (by difference in proportions), per se.

The cutoff was defined as that associated with delay in decision implementation based on Western cohorts (21) and may not necessarily be valid for Filipino cohorts. In our cohort, the correlation between readiness to implement a decision (as determined from the PtDA patient survey) and DCS was stronger with a cutoff of 20 (Spearman r=0.549) than with a cutoff of 25 (r=0.449). Bigger Filipino cohorts would be necessary to validate a more meaningful cutoff.

The mean post-intervention DCS was statistically lower in the experimental group (11.6 versus 19.3, P<0.07) (Table 2). Although not the protocol-defined parameter for the primary objective, this may suggest the effectiveness of the PtDA. The mean change in DCS in the two groups were similar; however, the range was wider for the experimental group, probably reflecting its multidimensional impact to users. The PtDA could help users be more confident with their decisions (decrease in DCS), or help them identify more points for consideration in making decisions (increase in DCS) and therefore stimulate further discussion with their family and doctors. Finally, the benefits of the PtDA may be more than just reducing delays in decision implementation; it could help improve patient satisfaction with their decisions and the decision-making process, as well as treatment compliance.

Utility in preparation for decision-making

More than 75% of the users reported a PDMS of ≥3.5, supporting its utility. Further, each PDMS item was scored at least a mean ≥3.5 and a median ≥4.0.

The highest scored utilities of the PtDA were: preparing to talk to their doctor regarding what matters to them (4.6); preparing to make a better decision (4.5); preparing to think about how involved they want to be in the decision (4.5); preparing for a follow-up visit with their doctor (4.5); and identifying questions they want to ask their doctor (4.4) (Table 3). These support the multidimensional utility of the PtDA, as discussed above.

Determinants of effectiveness and utility

Age, education, socioeconomic status and decision self-efficacy were studied as covariates to decisional outcomes and PtDA utility (Table 4). The demographic variables (age, education and socioeconomic status) did not correlate with DSES.

For the entire cohort, only DSES had moderate negative correlation with decisional conflict, which persisted only for the experimental group, on group analyses. In the control group, only the socioeconomic status was a strong determinant for decrease in decisional conflict, suggesting that family discussions alone are more likely to be sufficient when financial and logistic resources are ampler. In the experimental group, decision self-efficacy was a strong determinant for decisional conflict and PtDA utility.

Accounting for the effect of DSES as covariate, ANCOVA confirmed independent and large effects of both DSES and the PtDA on post-intervention DCS [supplementary file 5 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-5.pdf)].

Determinants of residual decisional conflict among PtDA users

In the experimental group, four had no residual decisional conflict (post-intervention DCS =0); six had residual decisional conflict (post-intervention DCS mean =19.3), including one with high DCS (=30). Patients with residual decisional conflict had significantly higher baseline DCS, lower DSES, and reported lower utility of the decision aid [supplementary file 5 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-5.pdf)].

To understand how cognitive and psychological factors determine residual decisional conflict, we compared the patient perspectives and values as reported in the PtDA values weighing scales between the groups with and without residual decisional conflict. Of the scales, only the attitude toward treatment was statistically different between the two groups, being higher in those without than those with residual decisional conflict (4.75 versus 4.00, P=0.09). Patients who were willing to do everything and were ready to deal with treatment side effects were more likely to have no residual decisional conflict after using the PtDA. Finally, patients with no residual decisional conflict gave higher utility scores for each item in the PDMS than did patients with residual decisional conflict.

Qualitative effects of the decision aid

To better understand the impact of the PtDA on patient decisions, we studied its qualitative effects based on the PtDA patient survey [supplementary file 5 (available at https://cdn.amegroups.cn/static/public/jhmhp-24-136-5.pdf)]. Overall, the decision aid did not change the proportion of the participants that were willing to get chemotherapy. Forty percent changed their decisions: 10%, from getting RT alone to getting RT plus alternative drug; 10%, from getting RT plus alternative drug to getting RT and standard drug (cisplatin); and 20%, from getting RT and standard drug to getting RT alone.

The proportion of participants who reported having reached a decision increased from 70% to 80% (in the control group, 63% to 63%), and those who have reached a decision and were ready to implement increased from 50% to 80% (in the control group, 50% to 25%). Post-intervention, the proportion who have reached a decision and were ready to implement was significantly higher for the experimental group (80% versus 25%, P<0.01).

Summary of findings and implications

Our findings suggest that the use of PtDA in a shared decision-making patient workflow can be effective in reducing decisional conflict, based on post-hoc analyses (mean post-intervention DCS) and was utile for decision-making. Decision self-efficacy, but not age, educational attainment, or socioeconomic status, was a strong determinant of decisional conflict and of PtDA utility.

Our findings could inform the development of shared decision-making patient workflows and integration of PtDA use. A multidisciplinary approach and shared decision-making culture must be in place. These could also inform identification of patients for whom the PtDA would be most useful and those for whom the PtDA must be combined with active coaching (10,34). Since active coaching would require additional personnel resource requirements, the DSES tool may be used to identify patients with low decision self-efficacy who could benefit from active coaching.

Limitations and future directions

Our study evaluated the effectiveness and utility of a PtDA within a defined workflow for shared decision-making. Therefore, the study was carried out in three private centers with similar workflows, limiting its applicability in other settings. The PtDA needs to be tested in more patients and in different centers and settings to further evaluate its effectiveness and understand its effect on decision-making.

Our study investigated short-term effects decisional outcomes, but did not investigate decision implementation and compliance outcomes. A follow-up study investigating these outcomes could better define the effectiveness and utility of the PtDA and validate a more meaningful DCS cutoff in Filipinos.

Our study explored the impact of age, educational attainment, and socioeconomic status on decisional outcomes, but did not explore the impact of health literacy, which has been shown to determine decision self-efficacy and other decisional outcomes and behavior of cancer patients (35-37) and caregivers (38). A follow-up study could explore health literacy to inform improvement and use of the PtDA (39).

Finally, to further enhance the utility or increase the uptake of the PtDA, an electronic interactive version may be developed by integrating artificial intelligence and user-centered design (40); the resource could present more graphics and more or fewer details depending on the learning style of the user. A Filipino version or a simplified version may be developed to address language restrictions or to account for lower health literacy levels.

Conclusions

The CECIL PtDA reduces mean decisional conflict scores and is useful in preparation for decision-making. Decision self-efficacy is a strong determinant for decisional conflict and PtDA utility. These findings are based on a defined clinical setting and a small sample and must be validated in other clinical settings and bigger studies. A multidisciplinary approach and shared decision-making culture must be in place when integrating the decision aid in the workflow. The DSES tool may identify patients who may require other decision support intervention such as active coaching.

Acknowledgments

We thank the participants in this study for their invaluable contribution. We acknowledge and thank Prof. Consuelo Suarez and Prof. Ivan Gomez of the University of Santo Tomas-Graduate School for their critical inputs and guidance.

Footnote

Reporting Checklist: The authors have completed the CONSORT checklist. Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-136/rc

Trial Protocol: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-136/tp

Data Sharing Statement: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-136/dss

Peer Review File: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-136/prf

Funding: This work was partly subsidized by the Philippine Council for Health and Research Development which has no role in the development and design of any aspect of the prototype development and evaluation or influence over any decision relating to the conduct of the study and writing and publication of the study report.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-136/coif). W.B. reports serving as the Vice President of Philippine Society of Oncologists, Inc. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was reviewed and approved by the Research Ethics Committee of University of Santo Tomas Hospital (REC-2023-02-003-MD), the Institutional Review Board of Manila Doctors Hospital (MDH IRB 2023-003_II-C), and the Ethics Review Committee of the University of the East Ramon Magsaysay Memorial Medical Center Inc. Research Institute for Health Sciences (1526/E/2023/098), and informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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