Quality of patient-reported outcome reporting and related trial characteristics in randomized controlled trials of cancer pain: A systematic review based on the CONSORT-PRO extension.

Introduction

The global incidence and mortality of cancer continue to increase, imposing a substantial disease burden. 1 Pain, as one of the most common and distressing symptoms among patients with cancer, can occur at all stages of the disease, with a reported prevalence of 60%–80% in patients with advanced cancer, and severely compromises quality of life. 2 Cancer pain refers to an unpleasant sensory and emotional experience associated with actual or potential tissue damage caused by malignant tumors or their treatment. 3 Compared with non-cancer pain, cancer-related pain is characterized by more complex and multidimensional features, including background pain, breakthrough pain, neuropathic pain, and treatment-related pain, which not only impair physical functioning but also exacerbate psychological distress such as anxiety and depression, further reducing health-related quality of life (HRQoL). 2 , 4 Therefore, validated patient-reported outcome measures (PROMs) capable of capturing multidimensional pain experiences are required for dynamic assessment. 5

Patient-reported outcomes (PROs) are measurements of any aspect of a patient's health status that come directly from the patient, without interpretation by clinicians or anyone else. 6 They are an important component of the evaluation of cancer treatments and supportive care interventions. 7 In recent years, the value of PROs in oncology clinical research has been increasingly recognized. 8 Professional and regulatory bodies such as the EMA, 9 the ASCO 10 and the ESMO 11 have issued policy and position statements recommending the routine inclusion of PROs in oncology randomized controlled trials (RCTs) to support patient-centered decision-making and to inform symptom monitoring, intervention adjustment, and follow-up management by health care professionals.

In cancer symptom management, many decisions rely on patients' subjective experiences; however, because pain is inherently subjective, discrepancies frequently exist between clinicians' assessments and patients' actual experiences, and reliance on objective indicators alone may underestimate the true symptom burden. 12 Multidimensional PROMs offer higher precision and a richer amount of information, making them suitable for identifying differences, complex types of function, and multidimensional concepts. Their flexibility allows for customized measurement of patient symptoms and preferences. 13 Consequently, multiple PROMs are commonly used to quantify PROs in research to capture patients' perspectives on symptom experiences and functional changes during treatment. 5 In some high-quality RCTs, PROs serve as primary or secondary endpoints and are used to evaluate the effects of interventions on symptom improvement, quality of life, and patient satisfaction. 14 , 15 Incorporating PROs into clinical trials of cancer pain not only helps health care professionals better understand patients' experiences during treatment and facilitates effective communication between patients and clinicians, but also provides an important evidence base for oncology nurses in symptom assessment, patient education, supportive care decision-making, and adjustment of pain management strategies. 7

Although PROs have been widely used in cancer-related RCTs, existing evidence indicates clear deficiencies in their design and reporting. In a study of overall HRQoL in patients with recurrent ovarian cancer, the analysis and interpretation of PROs were limited by the absence of pre-specified hypotheses. Furthermore, the inappropriate selection of PRO endpoints and assessment instruments contributed to the finding of no significant differences. 16 In many trials, information on the background and rationale for including PROs is missing, PROs are used in a non-standardized way, and the methods of assessment are not sufficiently justified. These issues may limit the use of PROs in clinical decision-making and evidence-based practice. 17 Moreover, missing PRO data are a common challenge in cancer trials. Such missingness may reflect “informative missingness” due to disease progression, treatment discontinuation or death, or “avoidable missingness” resulting from non-adherence to study procedures or administrative delays. In either case, if missing data are not fully reported and appropriately handled, they may introduce systematic bias and limit the interpretability and generalizability of the study findings, 18 , 19 making it difficult for nursing professionals to effectively translate trial evidence into symptom management and individualized supportive care decisions.

To improve the reporting completeness of PROs in RCTs, the Consolidated Standards of Reporting Trials for PRO (CONSORT-PRO) extension provides key reporting recommendations for trials that include PROs, requiring that study protocols and final published reports clearly describe PRO hypotheses, endpoints, methods, and analytical approaches. 20 However, the current status of the completeness of PRO reporting in cancer pain RCTs remains insufficiently understood. Therefore, this study conducted a systematic review based on the CONSORT-PRO extension to evaluate the reporting completeness of PROs in RCTs of cancer pain and to descriptively explore the distribution of reporting completeness across trial characteristics, with the aim of enhancing the interpretability and clinical applicability of future cancer pain trials.

Methods

Literature search

We searched CNKI (China National Knowledge Infrastructure), SinoMed, VIP (Chinese Science and Technology Journal Database), Wanfang, PubMed, the Cochrane Library, and Embase for RCTs of cancer pain. The search was limited to articles published in Chinese or English from 1 January 2015 to 1 March 2026. The search was initially conducted before submission and updated on 1 March 2026 before final analysis. A sample search strategy for PubMed is shown in Table 1 . The search strategy is provided in Supplementary File 1 . Table 1 Search strategy used in the study (PubMed example). Table 1 Database Search strategy PubMed #1 "cancer pain" [MeSH terms] OR "cancer-related pain" [Title/Abstract] OR "cancer associated pain" [Title/Abstract] OR "neoplasm-related pain" [Title/Abstract] OR ("cancer" [Title/Abstract] OR "neoplasm" [Title/Abstract]) AND "pain" [Title/Abstract] #2 "patient reported outcome measures" [MeSH terms] OR "patient reported outcome∗" [Title/Abstract] OR "PRO" [Title/Abstract] OR "PROMIS" [Title/Abstract] #3 "randomized controlled trial" [Publication type] OR "randomized controlled trials as topic" [MeSH terms] OR "random∗ controlled trial∗" [Title/Abstract] OR "random∗ trial∗" [Title/Abstract] #4: #1 AND #2 AND #3 AND filters: from 1 January 2015 to 1 March 2026

Study inclusion

Studies were eligible if they met the following criteria: (1) RCT design; (2) All included patients had cancer pain or were part of RCTs specifically targeting cancer pain management; (3) Any type of intervention or therapeutic approach for cancer pain; (4) Cancer pain measured as a primary or secondary outcome using PROs.

Studies were excluded if they met any of the following criteria: (1) full text unavailable; (2) non-RCT designs, including conference abstracts, study protocols, cohort studies, systematic reviews, case reports or case discussions, and cross-sectional studies; (3) duplicate publications, retracted articles or errata.

Data extraction

The literature search, study selection and data extraction were independently performed by two trained researchers according to the predefined inclusion and exclusion criteria. Any disagreements were resolved through discussion with a third researcher, who acted as arbiter.

All retrieved records were imported into EndNote 21, where duplicate publications were removed. Titles and abstracts were screened to exclude studies that did not meet the inclusion criteria. Full texts of potentially eligible articles were then reviewed to confirm eligibility, and studies that met all criteria were finally included. For included studies that reported PRO outcomes, the reporting completeness was evaluated using the CONSORT-PRO extension.

A data extraction form was created in Excel 2024. Extracted information included: article title, first author, year of publication, type of PRO instrument, type of intervention, sample size, study center (single- or multi-center), industry sponsorship, type of blinding, type of PRO outcome (primary or secondary), follow-up duration, CONSORT statement reporting and journal impact factor (IF, the impact factor of the journal in the year of publication).

Assessing PRO reporting completeness

The CONSORT-PRO extension was used to evaluate the reporting completeness of RCTs, and the scoring method was adapted from the approach published by Mercieca-Bebber et al. in 2017. 21 For each RCT report, 18 CONSORT-PRO items were assessed. Item 4a (whether PROs were used in eligibility criteria or stratification) was excluded. Item 7a (sample size calculation for PROs) was assessed only for RCTs in which PROs were specified as primary outcomes.

For each checklist item, the maximum score (1 or 0.5 point) was awarded if the required information was reported in the RCT, with the exception of item P1b. For item P1b, a score of 1 point was given if the abstract reported PROs and clearly specified them as primary or secondary outcomes; a score of 0.5 point was given if PROs were mentioned but the outcome status was not specified; and a score of 0 was given if PROs were not mentioned in the abstract.

Accordingly, when PROs were primary outcomes, the maximum total score was 15 points; when PROs were secondary outcomes, the maximum total score was 14 points. An item was regarded as completely reported if it received the maximum score; otherwise, it was considered incompletely reported. For each study, a percentage completeness score was calculated by dividing the sum of item scores by the corresponding maximum total score, and this percentage was used to reflect the quality of PRO reporting in RCTs. PRO reporting was classified as “good” when the CONSORT-PRO completeness score was greater than 80%, “moderate” when it was between 50% and 79%, and “poor” when it was less than 49%. 21

Risk of bias assessment

The risk of bias of the included RCTs was assessed using the Cochrane Risk of Bias 2.0 tool. Five domains were evaluated: bias arising from the randomization process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in measurement of the outcome, and bias in selection of the reported result. Each domain and the overall risk of bias were judged as low risk, some concerns, or high risk. The assessment was conducted independently by two reviewers, and disagreements were resolved through discussion.

Statistical analysis

Statistical analyses were performed using SPSS version 26.0. Descriptive statistics were used to summarize the data, with continuous variables expressed as mean ± SD and categorical variables presented as frequencies and percentages [ n (%)]. To explore the distribution of CONSORT-PRO reporting completeness across trial characteristics, descriptive subgroup analyses were conducted. For categorical characteristics, mean reporting scores were compared between subgroups. For continuous variables, including sample size and journal impact factor (IF), data were dichotomized into two groups based on their respective median values to facilitate descriptive comparison. Given the exploratory nature of this study and the small sample size, no formal inferential statistical testing was performed, focusing instead on identifying observed trends in reporting quality.

Results

Screening results

A total of 3455 records were identified through the literature search and imported into EndNote 21, where 1394 duplicate records were removed. According to the inclusion and exclusion criteria, 1985 records were excluded after screening titles and abstracts. After full-text review and further screening, 20 studies were finally included. The study selection process and results are shown in Fig. 1 . Fig. 1 PRISMA flow diagram of study selection. PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses.

Characteristics of RCTs

A total of 20 RCTs involving 3841 participants were included. All studies reported at least one PRO outcome. In 14 trials (70%), PROs were specified as primary outcomes, and in 6 trials (30%) they were specified as secondary outcomes. For pain measurement, 15 trials (75%) used the BPI or BPI-SF, and 5 trials (25%) used the NRS or NRPS to assess pain intensity. In addition to pain scales, several studies also used generic or domain-specific PRO instruments, such as the PROMIS scales, EORTC QLQ-C30, FACT-G, EQ-5D, HADS, GAD-7 and PHQ-8, to evaluate health-related quality of life, emotional symptoms and functional status. Overall, most RCTs combined pain scales with quality-of-life or psychological scales to capture the multidimensional impact of cancer pain interventions on patient outcomes.

With respect to study design, 10 trials (50%) were single-center studies and 10 trials (50%) were multicenter studies. 13 trials (65%) reported industry funding, whereas 7 trials (35%) did not report industry funding. Most trials were open-label: 13 studies (65%) used non-blinded designs, and only a few used single-blind or double-blind designs. 15 RCTs (75%) explicitly reported adherence to the CONSORT statement in the Methods section. The general characteristics of the included studies are presented in Table 2 . 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 Table 2 General characteristics of included randomized controlled trials. Table 2 No. Author Year PRO instruments Intervention (broad category) Sample size Study center Industry funding reported Blinding PRO endpoint type Follow-up duration CONSORT statement reported IF T C 1 Agarwal, N. 22 2021 BPI; BFI Pharmacological Placebo 1052 Multicenter Yes Double-blind Secondary 88 weeks No 6.60 2 Bell, T. 23 2016 BPI-SF Pharmacological Placebo 165 Multicenter Yes Open-label Secondary 4 weeks No 2.67 3 Epstein, A. S. 24 2023 BPI; BFI; ISI; PROMIS-GH Combined intervention Usual care 298 Multicenter No Single-blind Primary 26 weeks Yes 9.70 4 Groninger, H. 25 2024 BPI Treatment Standard treatment 127 Single center Yes Open-label Primary 24 h Yes 5.10 5 Hazard Vallerand, A. 26 2018 BPI; DT; MSAS; PPQ; SF-12; QOL; KPS; SOPA-C; PCS; CPAQ Nursing intervention Usual nursing care 310 Single center No Open-label Primary 12 weeks Yes 1.73 6 He, Y. 27 2021 NRS Combined intervention Usual care 30 Single center No Single-blind Primary 2 weeks Yes 2.40 7 Judge, M. K. M. 28 2021 MPQ; PMI Combined intervention Usual care 145 Multicenter No Open-label Secondary 1 week No 3.10 8 Kamdar, M. 29 2024 BPI; BQ-II; GAD-7; FACT-G; PHQ-8 Combined intervention Usual care 112 Single center Yes Open-label Primary 8 weeks Yes 3.50 9 Knoerl, R. 30 2021 NRS; PROMIS-PI; PROMIS-SF; PROMIS-ANX; PROMIS-DEP; PROMIS-FAT; PROMIS-PF; QLQ-CIPN20 Treatment Usual care 44 Single center Yes Open-label Secondary 8 weeks Yes 3.10 10 Lyu, Z. 31 2023 NRS; KPS; EQ-5D-3L Treatment Standard treatment 159 Multicenter No Double-blind Primary 5 weeks Yes 3.00 11 Mao, J. J. 32 2021 BPI; PROMIS-GH Treatment Standard treatment 360 Multicenter No Open-label Primary 24 weeks Yes 28.40 12 Mosley, S. A. 33 2023 BPI-SF; MDASI Pharmacological Placebo 87 Single center Yes Open-label Primary 8 weeks Yes 7.40 13 Pielkenrood, B. J. 34 2021 BPI; EORTC-QLQ-C15-PAL; EORTC-QLQ-BM22 Treatment Standard treatment 89 Single center Yes Open-label Secondary 12 weeks Yes 7.00 14 Raphaelis, S. 35 2020 BPI; BQII-G12; FESS; EORTC QLQ-C30 Nursing intervention Usual nursing care 153 Multicenter Yes Single-blind Primary 8 weeks Yes 4.64 15 Ryu, S. 36 2023 NRPS; FACT-G; BPI; EuroQOL-5 Treatment Standard treatment 339 Multicenter No Open-label Primary 21 weeks Yes 20.10 16 Valenta, S. 37 2022 BPI; CAS; FPQ; HADS; PPQ; SEQ; PMI Combined intervention Usual care 34 Multicenter Yes Single-blind Primary 6 weeks Yes 3.30 17 Winger, J. G. 38 2023 BPI-SF; PROMIS-PI; CPSS-PM; FACIT-Sp; GAD-7; PHQ-8; HAIQ Nursing intervention Usual nursing care 60 Single center Yes Open-label Secondary 10 weeks Yes 3.50 18 Yang, J. 39 2019 NRS; EORTC QLQ-C30; patient satisfaction questionnaire Combined intervention Standard treatment 58 Single center Yes Open-label Primary 4 weeks No 4.77 19 Zhang, L. 40 2021 BPI; MMAM Combined intervention Standard treatment 100 Single center Yes Open-label Primary 4 weeks No 5.00 20 Basch EM. 41 2019 BPI; NCI PRO-CTCAE Pharmacological Placebo 119 Multicenter Yes Double-blind Primary 12 weeks Yes 20.09 The numbers shown in this table correspond to the references listed in the manuscript's reference list (References 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ). Full bibliographic details can be found in the reference list. Intervention type was categorized as pharmacological, treatment, nursing intervention, or combined intervention according to the main intervention component reported in each trial. BPI, Brief Pain Inventory; BFI, Brief Fatigue Inventory; BPI-SF, Brief Pain Inventory-Short Form; ISI, Insomnia Severity Index; PROMIS-GH, Patient-Reported Outcomes Measurement Information System Global Health; DT, Distress Thermometer; MSAS, Memorial Symptom Assessment Scale; PPQ, Pain Profile Questionnaire; SF-12, Short Form Health Survey; QOL, Quality of Life; KPS, Karnofsky Performance Status; SOPA-C, Short-Form Social Support Scale; PCS, Pain Catastrophizing Scale; CPAQ, Chronic Pain Acceptance Questionnaire; NRS, Numeric Rating Scale; MPQ, McGill Pain Questionnaire; PMI, Pain Management Index; BQ-II, Brief Questionnaire-II; GAD-7, Generalized Anxiety Disorder-7; FACT-G, Functional Assessment of Cancer Therapy-General; PHQ-8, Patient Health Questionnaire-8; PROMIS-PI, Patient-Reported Outcomes Measurement Information System Pain Intensity; PROMIS-SF, Patient-Reported Outcomes Measurement Information System Short Form; PROMIS-ANX, Patient-Reported Outcomes Measurement Information System Anxiety; PROMIS-DEP, Patient-Reported Outcomes Measurement Information System Depression; PROMIS-FAT, Patient-Reported Outcomes Measurement Information System Fatigue; PROMIS-PF, Patient-Reported Outcomes Measurement Information System Physical Functioning; QLQ-CIPN20, Quality of Life Questionnaire-Chemotherapy Induced Peripheral Neuropathy 20; EQ-5D-3L, EuroQol 5-Dimensions 3-Level; MDASI, M. D. Anderson Symptom Inventory; EORTC QLQ-C15-PAL, European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C15 for Palliative Care; EORTC QLQ-BM22, European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Bone Metastases 22; BQII-G12, Brief Questionnaire-II G12; FESS, Pain Self-Efficacy Questionnaire-German version; EuroQOL-5, EuroQol 5 dimensions; CAS, Cancer-related Fatigue Scale; FPQ, Fatigue and Pain Questionnaire; SEQ, Symptom Experience Questionnaire; CPSS-PM, Chronic Pain Self-efficacy Scale - Pain Management; FACIT-Sp, Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale; HAIQ, Health Assessment and Impact Questionnaire; MMAM, Modified Medication Adherence Measure; NCI PRO-CTCAE, National Cancer Institute PRO version of the Common Terminology Criteria for Adverse Events; T, treatment group; C, control group; IF, Journal impact factor.

Completeness of PRO reporting

Based on the CONSORT-PRO extension, the 20 included studies were assessed for PRO reporting completeness, and the percentage completeness of reporting for each study is shown in Fig. 2 . PROs were specified as primary outcomes in 14 trials (70%) and as secondary outcomes in 6 trials (30%). Overall, the most completely reported items were P6aii, 13ai, 17ai and P21, each with a completeness rate of 80%, 85%, 85% and 85%. Items P2bi and P2bii were fully reported in only 6 trials (30%), item 18 in 10 trials (50%), and item P20 in 8 trials (40%), indicating the lowest overall adherence. Compared with trials in which PROs were primary outcomes, trials in which PROs were secondary outcomes showed clearly poorer reporting for P1b (abstract-explicitly stating PROs as primary or secondary outcomes) and P22 (relationship between PROs and clinical outcomes). The completeness of reporting for each item is presented in Table 3 . Fig. 2 Reporting completeness of included studies. Table 3 Completeness of PRO reporting based on the CONSORT-PRO extension. Table 3 CONSORT-PRO checklist item Primary endpoint ( n = 14) Secondary endpoint ( n = 6) All trials ( n = 20) Complete n (%) Incomplete n (%) Complete n (%) Incomplete n (%) Complete n (%) Incomplete n (%) P1b: Abstract - PRO noted as primary/secondary endpoint 10 (71.43) 4 (28.57) 2 (33.33) 4 (66.67) 12 (60.00) 8 (40.00) 2a: Rationale for including PRO 9 (64.29) 5 (35.71) 5 (83.33) 1 (16.67) 14 (70.00) 6 (30.00) P2bi: PRO hypothesis present 6 (42.86) 8 (57.14) 0 (0.00) 6 (100.00) 6 (30.00) 14 (70.00) P2bii: PRO domains specified in hypothesis 6 (42.86) 8 (57.14) 0 (0.00) 6 (100.00) 6 (30.00) 14 (70.00) P6ai: Evidence of PRO instrument validity provided/cited 10 (71.43) 4 (28.57) 5 (83.33) 1 (16.67) 15 (75.00) 5 (25.00) P6aii: Statement of the person completing the PRO (e.g. ‘patients completed’, or ‘self-report') 12 (85.71) 2 (14.29) 4 (66.67) 2 (33.33) 16 (80.00) 4 (20.00) P6aiii: Mode of administration specified (paper, e-PRO) 10 (71.43) 4 (28.57) 3 (50.00) 3 (50.00) 13 (65.00) 7 (35.00) 7a: How sample size was determined. Not required for PRO unless it is a primary study outcome∗ 11 (78.57) 3 (21.43) / / 11 (78.57) 3 (21.43) P12a: Statistical approach for dealing with missing data specified (imputation, omission of cases with missing data) 9 (64.29) 5 (35.71) 3 (50.00) 3 (50.00) 12 (60.00) 8 (40.00) CONSORT-PRO checklist item Primary endpoint ( n = 14) Secondary endpoint ( n = 6) All trials ( n = 20) Complete n (%) Incomplete n (%) Complete n (%) Incomplete n (%) Complete n (%) Incomplete n (%) 13ai: Report number of questionnaires submitted/available for analysis at baseline 13 (92.86) 1 (7.14) 4 (66.67) 2 (33.33) 17 (85.00) 3 (15.00) 13aii: Report number of questionnaires submitted/available for analysis principle time point for analysis 12 (85.71) 2 (14.29) 4 (66.67) 2 (33.33) 16 (80.00) 4 (20.00) 15: Demographics table includes baseline PRO 9 (64.29) 5 (35.71) 4 (66.67) 2 (33.33) 13 (65.00) 7 (35.00) 16: Number of patients (denominator) included in each PRO analysis and whether this was intention to treat 9 (64.29) 5 (35.71) 4 (66.67) 2 (33.33) 13 (65.00) 7 (35.00) 17ai: PRO results reported for the hypothesised domains and time point specified in the hypothesis –OR- reported for each domain of the PROM if no PRO hypothesis provided 12 (85.71) 2 (14.29) 5 (83.33) 1 (16.67) 17 (85.00) 3 (15.00) 17aii: Results include confidence intervals, effect size or some other estimate of precision 10 (71.43) 4 (28.57) 5 (83.33) 1 (16.67) 15 (75.00) 5 (25.00) 18: Results of any subgroup/adjusted/exploratory analyses are reported 7 (50.00) 7 (50.00) 3 (50.00) 3 (50.00) 10 (50.00) 10 (50.00) P20: PRO study limitations provided 5 (35.71) 9 (64.29) 3 (50.00) 3 (50.00) 8 (40.00) 12 (60.00) P21: Implications of PRO results for generalizability, use in clinical practice 11 (78.57) 3 (21.43) 6 (100.00) 0 (0.00) 17 (85.00) 3 (15.00) P22: PROs interpreted in relation to clinical outcomes 10 (71.43) 4 (28.57) 1 (16.67) 5 (83.33) 11 (55.00) 9 (45.00) CONSORT-PRO, Consolidated Standards of Reporting Trials for Patient-Reported Outcomes; PROMs, patient-reported outcome measures. ∗Item 7a was assessed only in RCTs with PROs specified as primary outcomes.

Descriptive exploration of PRO reporting completeness across trial characteristics

Given the small sample size ( n = 20), descriptive subgroup analyses were conducted to explore the distribution of CONSORT-PRO reporting completeness across different trial characteristics, rather than conducting formal inferential testing. The results revealed several notable trends. RCTs published after 2022 exhibited a higher mean completeness score (75.54 ± 8.60) compared to those published in 2022 or earlier (60.15 ± 9.64). Similarly, trials with follow-up durations of 5–12 weeks showed a higher mean score (70.07 ± 9.26) than those with follow-up durations of ≤ 4 weeks (56.15 ± 9.35). Notably, studies that explicitly reported adherence to the CONSORT statement in the Methods section achieved a substantially higher mean completeness score (70.27 ± 8.47) than those that did not (51.33 ± 8.51). Other trial characteristics, such as sample size and journal impact factor, showed minimal differences in reporting completeness when compared by their median values. These findings suggest potential areas for improvement, although these trends are exploratory and require further validation in larger study cohorts ( Table 4 ). Table 4 Distribution of CONSORT-PRO reporting completeness by trial characteristics. Table 4 Characteristics Total n (%) Mean ± SD (%) Year of publication ≤ 2022 13 (65.00) 60.15 ± 9.64 > 2022 7 (35.00) 75.54 ± 8.60 Sample size ≤ 123 10 (50.00) 66.40 ± 12.41 > 123 10 (50.00) 64.47 ± 11.72 Study center Single center 10 (50.00) 63.05 ± 11.54 Multicenter 10 (50.00) 68.02 ± 12.09 Industry funding No 7 (35.00) 68.54 ± 10.77 Yes 13 (65.00) 63.92 ± 12.40 Blinding Open-label 13 (65.00) 65.71 ± 12.58 Single-blind 4 (20.00) 70.00 ± 7.20 Double-blind 3 (15.00) 58.81 ± 13.58 Intervention type Combined intervention 7 (35.00) 62.35 ± 13.34 Nursing intervention 3 (15.00) 72.94 ± 8.14 Pharmacological 4 (20.00) 61.73 ± 17.35 Treatment 6 (30.00) 68.09 ± 6.36 PRO endpoint Secondary 6 (30.00) 60.12 ± 13.63 Primary 14 (70.00) 67.86 ± 10.59 Follow-up duration ≤ 4 weeks 6 (30.00) 56.15 ± 9.35 5–12 weeks 10 (50.00) 70.07 ± 9.26 ≥ 13 weeks 4 (20.00) 68.27 ± 14.90 CONSORT statement cited No 5 (25.00) 51.33 ± 8.51 Yes 15 (75.00) 70.27 ± 8.47 IF median ≤ 4.71 10 (50.00) 66.69 ± 9.73 > 4.71 10 (50.00) 64.38 ± 13.98 CONSORT-PRO, Consolidated Standards of Reporting Trials for Patient-Reported Outcomes; IF, impact factor; SD, standard deviation.

Risk of bias of included studies

The risk of bias of the 20 included RCTs was evaluated using the Cochrane Risk of Bias 2.0 tool across five domains and overall bias. 9 studies (45%) were rated as low risk, 6 studies (30%) as having some concerns, and 5 studies (25%) as high risk. At the domain level, the majority of trials demonstrated low risk in the randomization process (17/20), deviations from intended interventions (19/20), missing outcome data (17/20), and selection of the reported result (18/20). Variability was more apparent in the measurement of the outcome, with 11 studies rated as low risk, 4 as some concerns, and 5 as high risk, reflecting potential methodological limitations in how outcomes were measured in some trials. Detailed results are shown in Table 5 . Table 5 Risk of bias assessment of the included studies. Table 5 Domain Low Some concerns High Randomization process 17 3 0 Deviations from intended interventions 19 1 0 Missing outcome data 17 2 1 Measurement of the outcome 11 4 5 Selection of the reported result 18 2 0 Overall bias 9 6 5

Discussion

Main findings

Based on the CONSORT-PRO extension, this study systematically evaluated the completeness of PRO reporting in RCTs of cancer pain published from 2015 to 1 March 2026, a time frame selected to ensure the timeliness of the evidence, improve the comparability of included studies in terms of reporting practices, study design, and the use of PROs, and take into account the time required for the dissemination and implementation of the CONSORT-PRO guideline after its publication. Among the 20 included studies, 14 (70%) specified PROs as primary outcomes, and the overall reporting completeness rate was 65.65%, indicating a moderate level; this suggests that PRO reporting in cancer pain RCTs remains suboptimal, with marked deficiencies observed in several key items. The overall level of reporting completeness was broadly comparable to that reported in previous studies in other disease areas. 42 , 43 , 44 These findings indicate that inadequate PRO reporting is a common problem across disease areas, whereas the priorities for improvement in the cancer pain field require further clarification.

Implications for nursing practice and research

This study found that only 6 trials (30%) reported explicit PRO hypotheses, and no trial reported such hypotheses when PROs were specified as secondary outcomes. Trials in which PROs were primary outcomes showed higher PRO reporting completeness for this item than those in which PROs were secondary outcomes; however, even among trials with PROs as primary outcomes, more than half did not prespecify PRO hypotheses. Calvert et al. 20 noted that, in the absence of prespecified hypotheses, investigators are more likely to selectively report statistically significant findings from multiple analyses, which may not accurately reflect the overall study conclusions. Griffin Hughes et al. 45 further suggested that when selective outcome reporting occurs in published studies, clinicians can only make treatment decisions based on limited and incomplete information, thereby constraining the accurate interpretation of intervention effects. Because pain outcomes are influenced by multiple factors, including tumor stage, analgesic medications, psychological factors, and treatment phase, failure to specify PRO hypotheses, key measurement domains, and primary comparisons at the trial stage may increase ambiguity in subsequent statistical analyses and interpretation, thereby weakening the credibility of the evidence. This issue is particularly relevant when PROs are secondary outcomes, as the absence of hypotheses and target domains may further diminish their value for efficacy evaluation and clinical translation. The ROB 2.0 assessment further showed that most included RCTs were methodologically sound in randomization, particularly regarding randomization, deviations from intended interventions, missing outcome data, and selection of reported results. Some variability was noted in outcome measurement, which may affect the interpretability of PROs. These results complement the CONSORT-PRO evaluation and underscore the importance of rigorous study design and transparent PRO reporting in future cancer pain trials.

The study also found that only 50% of trials reported any results from subgroup, adjusted, or exploratory analyses. Subgroup analysis is an important approach for understanding potential confounding factors and their interactions with the primary research focus. In a study of 21 RCTs in non-small cell lung cancer, Waisberg et al. reported that only 24.7% of trials conducted subgroup analyses, 46 suggesting that this limitation is common across oncology research. Patients with cancer pain are highly heterogeneous with respect to pain mechanisms, tumor stage, functional status, analgesic regimens, and psychological coping with pain. 47 , 48 If relevant analyses are neither prespecified in the protocol nor presented in the final report, readers and clinicians must rely on overall mean estimates, making it difficult to identify potential differences in benefits and risks across patient groups and increasing the risk of directly extrapolating conclusions to heterogeneous populations.

In addition, the completeness rate for reporting PRO-specific limitations and their implications for generalizability and clinical practice was 40%. Most trials focused their discussion on differences in pain scores or quality-of-life scores between intervention and control groups, 49 but less often examined how factors such as the measurement properties of the instruments, cultural and language adaptation, respondent burden, patterns of missing data, and the analgesic treatment context might influence the interpretation and generalizability of PRO results. In clinical care and follow-up, nursing professionals often need to judge and select instruments based on the target population and feasibility of implementation; adequately discussing the limitations of PRO instruments and their implementation may help guide appropriate instrument selection and interpretation, thereby improving the specificity and feasibility of cancer pain symptom management.

A key factor contributing to suboptimal PRO reporting completeness in cancer clinical trials is missing data. 50 In this study, PRO data were missing in 16 trials (80%); only 12 trials (60%) reported methods for handling missing data, and 17 trials (85%) did not provide explanations for the reasons underlying missingness. Evidence suggests that clearly reporting the proportion, reasons, and handling strategies for missing data in study protocols and published reports is important for readers to evaluate the reliability of study conclusions, which is particularly critical for patient care and follow-up management. 51 When missing data occur during follow-up or when the reasons for missingness are unclear, nursing professionals may have difficulty accurately assessing pain trajectories and the true extent of functional impairment, thereby affecting timely adjustment of analgesic regimens, adherence support, and risk monitoring. Therefore, studies should be designed, conducted, and reported to minimize the risk of missing PRO data, with strict adherence to the CONSORT-PRO checklist items. When handling missing data, assumptions should be prespecified, the feasibility and timeliness of data collection by health care professionals clearly defined, and appropriate statistical methods, such as multiple imputation, mixed-effects models, or sensitivity analyses, employed to mitigate the risk of bias. Previous studies have shown that involving experienced personnel in PRO data collection is crucial for both implementation and planning. 52

Descriptive subgroup analysis revealed a notable trend toward improved reporting quality over time, with RCTs published after 2022 achieving a higher mean completeness score (75.54 ± 8.60) than those published in 2022 or earlier (60.15 ± 9.64). This observation is consistent with the increasing dissemination of CONSORT-PRO, 53 SPIRIT-PRO, 17 and related methodological standards in oncology in recent years. 54 This suggests that the gradual adoption of normative reporting frameworks is translating into substantive improvements in reporting completeness. Furthermore, trials with follow-up durations of 5–12 weeks showed a higher mean score (70.07 ± 9.26) than those with durations of ≤ 4 weeks (56.15 ± 9.35), while trials with durations of ≥ 13 weeks also maintained a relatively high mean score (68.27 ± 14.90). Previous studies have suggested that overly long follow-up may be accompanied by increased loss to follow-up and missing data, which may increase the risk of biased results. 55 , 56 Taken together, these observed trends suggest that future cancer pain trials should balance outcome changes and the risk of missing data when determining follow-up duration and should emphasize prevention of missing data and transparent reporting of missingness during both the design and implementation phases. In addition, studies that reported adherence to the CONSORT statement exhibited substantially higher mean reporting completeness (70.27 ± 8.47) than those that did not (51.33 ± 8.51). This finding is consistent with previous research in the field of multiple sclerosis, 57 further supporting the positive role of reporting guidelines in improving trial quality. In the present review, 15 trials (75%) reported adherence to the CONSORT statement; however, none of the 20 included RCTs mentioned CONSORT-PRO. This indicates that although CONSORT is widely accepted as a basic framework for RCT reporting in the field of cancer pain, specific guidance for PRO reporting remains insufficiently emphasized. The CONSORT-PRO extension offers a structured framework to improve the quality of PRO use in clinical trials by guiding the design, conduct, and reporting of PRO-related components, thereby enhancing transparency and reproducibility in PRO reporting and interpretation. 58 Therefore, journals should underscore the importance of the CONSORT-PRO guideline and require future cancer pain RCTs to explicitly state adherence to CONSORT-PRO at the study design stage and to rigorously comply with its reporting requirements.

Limitations

This study has several limitations. First, only cancer pain clinical trials published within a specific time frame and reporting PROs as primary or secondary outcomes were included, resulting in a relatively small number of eligible RCTs and a potential risk of selection bias. Future studies could broaden the inclusion criteria to further examine the relationships between PRO reporting completeness and factors such as intervention effects and sample size. Second, the assessment was based solely on published articles; trial protocols or registration records were not systematically reviewed, which precluded evaluation of whether PRO-related content changed from protocol to publication. In addition, the exploratory analysis of potential characteristics associated with PRO reporting completeness may not have been exhaustive due to the small sample size, and future research should consider a more comprehensive set of influencing factors using larger cohorts. Meanwhile, researchers should be encouraged to proactively adhere to the CONSORT-PRO guideline at the study design stage, in order to promote overall improvements in the quality of reporting in cancer pain trials.

Conclusions

This study showed that, over the past decade, the overall reporting completeness of PROs in cancer pain RCTs was 65.65%, indicating a moderate level. This finding suggests that current reporting remains insufficient to fully support interpretation of patients’ symptom experiences and symptom-management evidence. In particular, shortcomings in prespecifying PRO hypotheses and target domains, reporting subgroup/adjusted/exploratory analyses, and describing the generalizability and clinical significance of PRO results suggested substantial room for improvement in PRO design, interpretation, and dissemination in cancer pain trials. Descriptive analysis within this study observed that publication after 2022, follow-up duration of 5–12 weeks, and an explicit statement of adherence to the CONSORT guidelines in the Methods section corresponded to higher mean scores of PRO reporting completeness. These trends indicate that standardized study design and reporting strategies could potentially improve the interpretability of PRO evidence. Future cancer pain RCTs should prespecify clinically meaningful PRO outcomes at the design stage and implement CONSORT-PRO requirements in reporting to enhance the applicability of study findings to symptom management and nursing practice.

CRediT authorship contribution

Yu Zhang: Conceptualization, Methodology, Formal analysis, Writing - Original Draft. Xia Li: Data Curation, Formal Analysis. Lujuan Wu: Formal analysis, Methodology, Visualization. Xianqi Wei: Supervision, Data Curation. Shiying Kang: Writing - Review & Editing. Jinxia Ding: Project Administration, Funding Acquisition. All authors have read and approved the final manuscript.

Ethics statement

Not required.

Data availability statement

Data available on request from the authors.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the authors used ChatGPT (OpenAI) in order to improve language expression and readability. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

Funding

This work was supported by the 10.13039/501100018684 National Health Commission Capacity Building and Continuing Education Center ( 10.13039/100005913 NHC Party School, Grant No. GWJJMB202510042091 ). The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Declaration of competing interest

The authors declare no conflict of interest.

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Supplementary materials

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Supplementary data to this article can be found online at https://doi.org/10.1016/j.apjon.2026.100983 .