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Participants | RECRUITMENT | The following participant groups were recruited for involvement in both the question submission and the Delphi prioritisation:Clinicians involved in neonatal care: neonatologists, paediatricians, trainee doctors, neonatal nurses and advanced neonatal nurse practitioners were contacted through professional organisations including the British Association of Perinatal Medicine (BAPM), the Neonatal Nurses Association and the Neonatal Society, through organisational websites, direct email correspondence with members, regional teaching and meetings and social media.AHPs involved in neonatal care: occupational therapists, physiotherapists, dietitians, speech and language therapists and clinical psychologists were contacted through the Association of Paediatric Chartered Physiotherapists, Royal College of Occupational Therapists, British Dietetic Association and Royal College of Speech and Language Therapists through websites, regional and national meetings and social media.Researchers: academics and researchers working within neonatology were contacted through the Neonatal Society, other existing research networks, regional and national meetings and through clinical trial units with a neonatal interest.Parents and former neonatal patients: parents, former patients and family members with experience of neonatal care were contacted through the national care coordinator groups, Maternity Voices Partnerships, relevant charity and advocacy websites and through social media.We requested and recorded basic background descriptive data from participants. By ongoing monitoring of these data throughout the study, we aimed to ensure representation across the different stakeholder groups and of diverse social and ethnic groups—targeting under-represented groups accordingly. Recruitment was international, with participants requested to have personal experience of neonatal care or research in high-income settings. | PMC10646876 | |
Question design and submission | ’ | A bespoke platform for question submission was devised using ‘OnlineSurvey’ (Jisc Services Limited, UK) software, with iterative development and face validity testing from all steering group members. The platform guided participants through the practicalities of structuring questions in the PICO format. We used categorical variables for gestational age and geographical location in the population (P) domain alongside a free-text field and used free-text fields for intervention (I) and comparison (C) domains. Outcomes could be selected from a categorical variable populated with the Core Outcomes in Neonatology
An example PICO question based on a well-known neonatal trial was displayed on the question submission platform.Pre-recorded video resources were developed for the BAPM website, showing members of the steering group putting together a PICO question relevant to their branch of practice. Links to these resources were included on the question submission software.Two BAPM-supported webinars were held, explaining the development of PICO questions: one targeted towards all participants and one specifically designed to support parents and former patients led by a parent representative.We contacted other groups who had undertaken neonatal priority setting work (for example, related to neonatal transport) directly and included relevant research questions in PICO format.Each submitted question was reviewed by two independent members of the steering committee to remove questions that were incomplete, duplicate, out of scope, unclear or already answered, prior to progression to the eDelphi. | PMC10646876 | |
Prioritisation process | All eligible research questions were entered into a three-round eDelphi survey using ‘DelphiManager’ (Comet Initiative Delphi Manager, University of Liverpool, UK) software, to establish a consensus as to their importance. Participants were asked to rank each research question on a 9-point Likert scale with 1 representing ‘no importance’ and 9 representing ‘critical importance’. After completion of round one, participants could suggest additional questions in PICO format which underwent the same review process as existing questions and were added to the second round of the eDelphi. Due to the large number of research questions, the second and third rounds of the eDelphi were limited to the top 75 and 50 ranked questions, respectively, to help minimise attrition rates. In the third round, the ranking by individual stakeholder group was displayed using the DelphiManager software (
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Parental and former patient involvement | To maximise accessibility for non-clinical participants, guidance was provided by the study steering group parent representative throughout the prioritisation process. Advice was sought from key advocacy organisations such as Bliss to determine how best to meaningfully involve parents and ex-neonatal patients while keeping questions specific enough to be addressed in interventional trials. In addition to the well-attended focused parental webinar already described, videos of sample PICO questions were recorded by different stakeholders including a parent with experience of neonatal care. Publicity for involvement in the Delphi stages of the questionnaire was supported by a range of organisations including Maternity Voices Partnerships, local parent groups and relevant advocacy and charitable groups. | PMC10646876 | ||
Results | The national neonatal priority setting partnership was completed as outlined in the study protocol. | PMC10646876 | ||
Question development | ’ | Two hundred and sixty-five questions were submitted in PICO format during the 1-month submission period, from a total of 108 participants. The most common themes for questions were feeding and nutrition (20%) and family integrated care (20%). Stakeholder group breakdown was 11% parents, 4% nurses, 49% doctors, 11% AHPs, 15% researchers and 11% other (Participant characteristics*‘Other’ not included as an option in the eDelphi survey.Flow chart of question identification and eDelphi consensus process. PICO, population, intervention, comparison, outcome. | PMC10646876 | |
eDelphi survey | MAY | The three-phase online Delphi survey opened in May and was completed in August 2022; over 200 participants registered their interest. One hundred and sixty-four questions were eligible for entry into the first round of the survey which was completed by 144 participants. Raw scores displayed a bimodal distribution when compared across stakeholder groups with a clear consensus regarding those deemed more important (Prioritisation of research questions by stakeholder groups across round two of the eDelphi.Thirty-seven new questions were submitted during round one of the eDelphi; 22 of these were deemed eligible for entry into round two. The results of round three displayed similar concordance between stakeholder groups, although with a higher consensus between the clinical groups (Stakeholder variability on round three of the eDelphi. Pairwise comparisons by stakeholder group of the ranked mean scores from round three for each outcome. Multiple pairwise comparisons presented together to aid visualisation. Comparisons arranged so that they are vertically or horizontally aligned to the stakeholder group label. | PMC10646876 | |
Final list of prioritised research questions | All eligible questions were amalgamated into a final list of prioritised research questions and can be viewed in
Final list of top 10 prioritised research questions | PMC10646876 | ||
Discussion | Using a robust, reproducible consensus methodology, we have identified and prioritised 186 neonatal research questions suitable for definitive interventional clinical trials. Through involvement of a broad range of stakeholders, the results are generalisable to the wider neonatal community in the UK. These results should inform the design of practice-changing clinical trials to ensure such trials address clinically relevant research questions and avoid contributing to research waste.This neonatal research priority setting partnership builds on previous priority setting work by Duley A strength of this project is the large numbers of participants: over 200 people from several different high-income countries identified and ranked research questions. Additional strengths include ongoing parent representation with the use of specially designed training materials and question submission software supporting involvement in designing PICO questions. Finally, the use of a well-established, transparent eDelphi methodology ensures that this process was robust and reproducible for use in future initiatives. This approach could be used to identify and prioritise research questions suitable for other methodologies such as qualitative research.A limitation of this work was attrition during the eDelphi survey, which was most notable among parents and former patients. Ensuring ongoing parent, patient or public participation in Delphi surveys is well recognised to be challenging.We recognised at the outset that meaningful involvement in prioritisation required complex medical and technical knowledge of neonatal medicine, and that this knowledge may not be easily accessible to parents and ex-neonatal patients. We did however endeavour to include parents and ex-neonatal patients as they are key stakeholders in research designed to resolve uncertainties about the use of existing treatments. A different process would be needed to prioritise RCTs of emerging new therapies at earlier stages of translation. Following engagement with our parental representative and the organisation charity Bliss, we attempted specific and targeted parental prioritisation using plain English summaries of the most highly ranked questions. However, even this approach was considered inappropriate by our parent representative and charity partners who concluded that for parental involvement to be truly meaningful, it should be addressed by a more targeted qualitative approach focused on smaller numbers of research questions. Therefore, while robust health professional input was obtained from the full range of neonatal clinical and allied professions, this process should be considered less representative of parent and ex-neonatal patient views.Priority setting work is becoming more widespread, with a recent scoping review showing that health-related topics encompassed 93% of all priority setting projects completed by the end of 2020.Future steps include sharing these prioritised research questions with clinical trial funders through existing commissioning processes. Our study methods and training materials strove to support detailed PICO question formation; however, we recognise some questions will require further refinement prior to evaluation in perinatal and neonatal adaptive trial platforms. Utilisation of priority setting results by research funders is expanding rapidly and there is variation in the methods used. | PMC10646876 | ||
Data availability statement | All data relevant to the study are included in the article or uploaded as supplemental information. All data relevant to this study are uploaded as supplemental information. | PMC10646876 | ||
Ethics statements | PMC10646876 | |||
Patient consent for publication | Not required. | PMC10646876 | ||
Ethics approval | Research Ethics Committee approval was not required as the study did not recruit participants. | PMC10646876 | ||
References | PMC10646876 | |||
Abstract | PMC10757135 | |||
Background | mCRC, toxicities, HFSR, hand‐foot skin reaction | METASTATIC COLORECTAL CANCER, HYPERTENSION | Fruquintinib has demonstrated significant improvement in overall survival (OS) among previously treated metastatic colorectal cancer (mCRC) patients. However, the utilization of fruquintinib has been constrained by various toxicities, such as hand‐foot skin reaction (HFSR) and hypertension, particularly in elderly patients with reduced tolerance to the standard dosage. This study aims to investigate the efficacy and safety of fruquintinib dose‐escalation strategy for elderly refractory mCRC patients. | PMC10757135 |
Patients and Methods | toxicity | This open‐label, single‐arm, phase II trial included patients aged 65 years or over with mCRC who had progressed after two or more lines of chemotherapy. Fruquintinib was administered for 21 consecutive days of a 28‐day treatment cycle. The starting dose of fruquintinib was 3 mg/day and escalated to 4 mg/day in Week 2 and 5 mg/day in Week 3 if no significant drug‐related toxicity was observed. The highest tolerated dose from Cycle 1 would be administered in Cycle 2 and all subsequent cycles. Before commencing treatment, all enrolled patients underwent a G8 questionnaire and comprehensive geriatric assessments. The primary endpoint of the study was progression‐free survival (PFS). | PMC10757135 | |
Results | hypertension, HFSR, diarrhea | ADVERSE EVENTS, HYPERTENSION | A total of 29 patients were enrolled and all started fruquintinib at 3 mg/day. Fifteen patients (51.7%) were subsequently escalated to 4 mg/day and 4 (13.8%) to 5 mg/day. Only four (13.8%) patients discontinued treatment due to adverse events (AEs). The median PFS was 3.8 months (95% CI, 2.7–4.9), and the median OS was 7.6 months (95% CI, 6.5–8.7). Treatment‐related adverse events (TRAEs) were observed in all 29 patients (100%). The most frequently occurring (>10%) TRAEs greater than Grade 3 were HFSR (20.7%), hypertension (20.7%), and diarrhea (10.3%). | PMC10757135 |
Conclusion | Our study indicated that a dose of 4 mg/day was well tolerated by most elderly patients, suggesting that fruquintinib dose‐escalation strategy during the first cycle could serve as a viable alternative to the standard 5 mg/day dosing.
Sirui Tan and Shunyu Zhang contributed equally to this work. | PMC10757135 | ||
INTRODUCTION | colorectal cancer, tumor, CRC, toxicity, cancer, various malignant tumors | COLORECTAL CANCER, TUMOR, ONCOGENESIS, CANCER, TUMOR ANGIOGENESIS, ONCOLOGY | Globally, colorectal cancer (CRC) ranks third in incidence and second in tumor‐related mortality among various malignant tumors in the world.Fruquintinib is a potent and highly selective small‐molecule inhibitor of vascular endothelial growth factor receptor (VEGFR)‐1, ‐2, and ‐3 that inhibit tumor angiogenesis.In clinical practice, physicians often use various dose reduction or interval regimens to address the challenges faced by elderly patients who may exhibit poor tolerance to treatments, despite the lack of supportive clinical data. It is noteworthy that these strategies draw inspiration from the utilization of regorafenib. Regorafenib, an oral multitargeted kinase inhibitor, blocks several protein kinases involved in angiogenesis, oncogenesis, and tumor microenvironment.The International Society of Geriatric Oncology has initially proposed that comprehensive geriatric assessment (GA) may help predict cancer treatment‐related toxicity and survival, as well as guide the choice and intensity of treatment.Here, we report the efficacy and safety of fruquintinib dose‐escalation strategy for elderly refractory mCRC patients. Meanwhile, this study explored whether GA can predict the efficacy of fruquintinib treatment in elderly patients with mCRC. | PMC10757135 |
METHODS | PMC10757135 | |||
Patients and study design | Tumors, active hepatitis, arrhythmia, Cancer | UNCONTROLLED HYPERTENSION, METASTASIS, ARRHYTHMIA, TUMORS, WEST, ONCOLOGY, HEART FAILURE, CORONARY ARTERY DISEASE, CANCER | This phase II prospective, single‐arm, open‐label, multicenter study was conducted at West China Hospital of Sichuan University, West China Fourth Affiliated Hospital of Sichuan University, Sichuan Cancer Hospital, and Sichuan Provincial People's Hospital. The study strictly adhered to the Helsinki provisions of the Declaration and obtained approval from the institutional review boards at each participating center. This trial is registered with The key inclusion criteria were as follows: (1) patients aged 65 years or older who were diagnosed with mCRC confirmed by histopathology; (2) refractory patients defined the patients who progressed after two or more lines of standard chemotherapy (irinotecan, oxaliplatin, and fluorouracil) according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1; concurrent administration of VEGF or epidermal growth factor receptor (EGFR) inhibitors during chemotherapy was permitted; (3) Eastern Cooperative Oncology Group (ECOG) performance status of 0 or l; (4) able to take oral medication and expected survival time of at least 3 months; (5) presence of at least one measurable lesion in accordance with RECIST version 1.1; (6) informed consent and completed geriatric questionnaires at the time of enrollment; and (7) adequate organ and bone marrow function up to 2 weeks before enrollment.The primary exclusion criteria included: (1) prior treatment with VEGFR inhibitors; (2) presence of central nervous system metastasis; (3) concurrent occurrence of uncontrolled hypertension, coronary artery disease, arrhythmia, heart failure, active hepatitis (defined as HBV DNA ≥10 | PMC10757135 |
Procedures | bleeding, hand‐foot skin reaction, toxicity, abnormal liver function, proteinuria, Depression, Cancer | ADVERSE EVENT, BLEEDING, DISEASE PROGRESSION, ADVERSE EVENTS, HYPERTENSION, CANCER | All included patients underwent GA and G8 screening tool before treatment. GA included Instrumental (IADL) and Activities in Daily Living (ADL) questionnaires, the Mini‐Nutritional Assessment (MNA), the Geriatric Depression Scale‐15 (GDS‐15), the Mini‐Mental State Examination (MMSE), the Cumulative Illness Rating Scale‐Geriatric (CIRS‐G) and Timed Up and Go (TUG) test.Fruquintinib was administered orally on 21 consecutive days in a 28‐day treatment cycle. All patients underwent dose escalation during the first cycle of fruquintinib treatment. The initial week involved oral administration of fruquintinib at a dosage of 3 mg/day. If this dosage was well tolerated, the dosage was increased to 4 mg/day during the second week. Subsequently, if the patient still exhibited tolerability, the dosage was further escalated to 5 mg/day during the third week. From the second cycle, patients were given the maximum dose that they had tolerated in the first cycle. CT scans were performed every two cycles for efficacy evaluation.AEs were recorded following the National Cancer Institute's Common Terminology Criteria for Adverse Events (CTCAE) version 4.0. Adjustments to the fruquintinib dosage were made during treatment based on the occurrence of adverse events. If patients exhibited hand‐foot skin reaction, proteinuria, hypertension, decreased platelet count, bleeding, or abnormal liver function, dose modifications were implemented according to previously established criteria.Criteria for patient withdrawal from the trial were as follows: (1) disease progression according to the (RECIST) 1.1 standard; (2) occurrence of unacceptable toxicity; (3) patient's request to withdraw from the trial; and (4) delay of more than 2 weeks in patient's treatment. | PMC10757135 |
Outcomes | death, Tumor, cancer, SD, PD | DISEASE PROGRESSION, DISEASE, CANCER, TUMOR | The primary endpoint was progression‐free survival (PFS) defined as the time from the start of treatment to the first verifiable disease progression or death due to cancer. Secondary endpoints were overall survival (OS), safety, and objective response rate (ORR). OS is defined as the time from the start of treatment to death from any cause. Tumor response was categorized as complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). ORR was determined by evaluating patients who achieved either CR or PR.Safety evaluation included AEs, laboratory tests, general physical examination, physical status score, electrocardiogram, etc. The investigator was responsible for taking corresponding treatment measures for AEs in patients. | PMC10757135 |
Statistical analysis | In the phase II REGOLD study, the median PFS was 2.2 months. With a PFS threshold of 2.2 months and an expected PFS of 4.0 months, simulation results indicated a sample size of 26 with Patient baseline characteristics were described. PFS and OS were estimated using Kaplan–Meier survival curves. The correlation between geriatric assessment and survival outcomes was evaluated by the Cox proportion hazard model. Statistical analyses were conducted using SPSS software. All statistical tests were two‐sided, and a significance level of | PMC10757135 | ||
RESULTS | PMC10757135 | |||
Patient characteristics | hypertension | PRIMARY TUMOR, LIVER METASTASES, HYPERTENSION, TYPE 2 DIABETES | Between November 6, 2020, and January 19, 2022, a total of 29 patients were enrolled in the study, and the cutoff date for OS was October 30, 2022. The median age of the patients was 69 years (range: 65–77), and 16 (44.8%) were male. Only 13.8% (4/29) of patients had an ECOG of 0. The primary tumor was located in the right colon in three cases (10.3%), in the left colon in 10 cases (34.5%), and in the rectum in 16 cases (55.2%). 79.3% (23/29) of patients underwent surgical resection of the primary tumor. Liver metastases (22/29) were the most common metastatic site. All patients received two or more previous chemotherapeutic regimens (median 2). Controllable hypertension (5/29; 17.2%) and type 2 diabetes (5/29; 17.2%) were the most common comorbidities. Most patients (27/29) had also received targeted therapy, with 82.8% (24/29) receiving bevacizumab and 10.3% (3/29) receiving anti‐EGFR monoclonal antibody. GA and G8 were performed for all patients at baseline. Detailed clinical characteristics, GA, and G8 information of the patients can be found in Table Baseline clinical characteristics and geriatric assessment. | PMC10757135 |
Treatment exposure and efficacy | Among 29 patients, 34.5% (10/29) patients had a maximum tolerated dose of 3 mg fruquintinib, 51.7% (15/29) patients had a maximum tolerated dose of 4 mg, and only 13.8% (4/29) patients could tolerate a therapeutic dose of 5 mg. The weekly dosing history for patients up to Week 1 of Cycle 3 is summarized in Figure Swimmer plot presenting dosing history up to Week 1 of Cycle 3.Maximum tolerable dose and efficacy with fruquintinib treatment.Survival outcomes with fruquintinib treatment. (A) The overall survival curve of the entire cohort. (B) The progression‐free survival curve of the entire cohort.Univariate analysis of progression‐free survival correlations in 29 patients using a Cox proportion hazard model.Univariate analysis of overall survival correlations in 29 patients using a Cox proportion hazard model. | PMC10757135 | ||
Safety | diarrhea, fatigue, decreased appetite, hypertension, hand‐foot syndrome | ADVERSE EVENTS, HYPERTENSION | Treatment‐related adverse events (TRAEs) were observed in all 29 patients (100%). Common AEs (>40%) included fatigue (23/29; 79.3%), decreased appetite (17/29; 58.6%), and hand‐foot syndrome (13/29; 44.8%). The most frequently occurring (>10%) TRAEs greater than Grade 3 were hand‐foot syndrome (6/29; 20.7%), hypertension (5/29; 17.2%), and diarrhea (3/29; 10.3%) as indicated in Table Treatment‐related adverse events. | PMC10757135 |
DISCUSSION | hypertension, colon cancer, fatigue | DISEASE PROGRESSION, HYPERTENSION, COLON CANCER | This study is the first to evaluate the efficacy and safety of fruquintinib initial dose‐escalation strategy for elderly patients with refractory mCRC. The mPFS in patients who were treated with this strategy was 3.8 months, and the primary reason for discontinuation of treatment was disease progression. The majority of elderly mCRC patients were able to tolerate a fruquintinib dosage of 4 mg/day, and fatigue was a major AE. Our study suggests that, for elderly patients with refractory mCRC, the fruquintinib dose‐escalation strategy could serve as a promising alternative to the standard 5 mg/day dosing.In the phase III FRESCO study, the average age of the study participants was 54.6 years.In the present study, a dose‐escalation strategy was implemented during the first cycle of treatment, revealing that the majority of elderly patients with mCRC could tolerate a dose of 4 mg/day. Despite the lower intensity dose administered in this study compared with the overall population in the FRESCO study, the survival outcomes observed were similar. The FRESCO study has reported an incidence of 61.1% for grade ≥3 AEs, with 15.1% discontinuing treatment due to AEs.Although hypertension is a frequently reported AE of anti‐VEGF/VEGFR drugs as shown in this study and previously published literature,Currently, limited research has been conducted to investigate the predictive value of GA in elderly colon cancer patients regarding the effectiveness of specific treatment regimens, and the findings have been controversial. A previous study has suggested that normal IADL is associated with better OS outcomes in elderly mCRC patients receiving first‐line therapy.Our study has several limitations, including a small sample size and a single‐arm design. Additionally, the comparison of data between our study and previous studies on regorafenib and TAS‐102 is challenging due to differences in research settings and studied populations. To provide more robust evidence, larger‐scale phase III clinical trials are necessary to validate the results obtained in this study. | PMC10757135 |
CONCLUSIONS | Our study indicated that fruquintinib weekly dose‐escalation strategy during the first cycle maintained its efficacy and its safety profile was tolerable. Physicians may consider this fruquintinib dose‐escalation strategy as a viable alternative to the standard 5 mg/day dosing in the management of elderly patients with refractory mCRC. | PMC10757135 | ||
AUTHOR CONTRIBUTIONS | PMC10757135 | |||
FUNDING INFORMATION | None. | PMC10757135 | ||
CONFLICT OF INTEREST STATEMENT | The authors have no conflict of interest. | PMC10757135 | ||
ACKNOWLEDGMENTS | Cancer | WEST, CANCER | We express our gratitude to West China Hospital of Sichuan University, West China Fourth Affiliated Hospital of Sichuan University, Sichuan Cancer Hospital, and Sichuan Provincial People's Hospital for their understanding of our research and the provision of data. | PMC10757135 |
DATA AVAILABILITY STATEMENT | The data that support the findings of this study are available from the corresponding author upon reasonable request. | PMC10757135 | ||
REFERENCES | PMC10757135 | |||
Background | PsA, tumor necrosis | PSORIATIC ARTHRITIS, TUMOR NECROSIS | Guselkumab is a selective interleukin (IL)-23 inhibitor targeting the IL-23p19 subunit. In the phase 3b COSMOS trial, guselkumab demonstrated efficacy in treating participants with active psoriatic arthritis (PsA) and inadequate response (IR; lack of efficacy or intolerance) to tumor necrosis factor inhibitors (TNFi). | PMC10428525 |
Methods | PsA, swollen joints, tumor necrosis, psoriasis | DISEASE, TUMOR NECROSIS, PSORIASIS | Adults with active PsA (≥ 3 swollen joints, ≥ 3 tender joints) and IR to one or two TNFi (TNFi-IR) were randomized 2:1 to guselkumab at Weeks 0, 4, then every 8 weeks (Q8W) or placebo➔guselkumab Q8W at Week 24 with possible early escape at Week 16. Levels of serum cytokines, including interferon γ (IFNγ), IL-10, and tumor necrosis factor α (TNFα); T helper 17 (Th17) effector cytokines IL-17A, IL-17F, and IL-22; and acute phase proteins C-reactive protein (CRP), IL-6, and serum amyloid A (SAA), were assessed and compared with demographically matched healthy controls; guselkumab pharmacodynamics through Week 24 were also assessed. Associations between baseline biomarker levels and 1) baseline disease activity (28-joint disease activity score using CRP [DAS28-CRP], psoriasis area and severity index [PASI], and % body surface area [BSA] affected by psoriasis) and 2) clinical response (including ≥ 20% improvement in American College of Rheumatology criteria [ACR20] response) at Week 24 were assessed. | PMC10428525 |
Results | psoriasis | PSORIASIS | Baseline serum levels of IL-6, IL-10, IL-17A, IL-17F, IL-22, TNFα, and IFNγ were significantly higher in COSMOS TNFi-IR participants than in healthy controls. Baseline IL-6, CRP, and SAA levels were associated with baseline DAS28-CRP. IL-17A and IL-17F levels were associated with baseline PASI score and psoriasis BSA. Baseline swollen or tender joint counts did not associate with baseline biomarker levels. At Week 24, significant decreases from baseline in CRP, SAA, IL-17A, IL-17F, and IL-22 levels were seen in guselkumab-, but not placebo-, treated participants. IL-17F and IL-22 levels at Week 24 in guselkumab-treated participants did not significantly differ from those of healthy controls. Guselkumab-treated participants achieving ACR20 response at Week 24 exhibited higher baseline IL-22 and IFNγ levels versus nonresponders. | PMC10428525 |
Conclusions | PsA, skin disease, arthritis | SKIN DISEASE, ARTHRITIS | Results from COSMOS participants with active, TNFi-IR PsA suggest guselkumab reduces levels of effector cytokines associated with the IL-23/IL-17 pathway, including those associated with baseline arthritis and skin disease activity. | PMC10428525 |
Trial registration | ClinicalTrials.gov: NCT03796858. | PMC10428525 | ||
Supplementary Information | The online version contains supplementary material available at 10.1186/s13075-023-03125-4. | PMC10428525 | ||
Keywords | PMC10428525 | |||
Background | PsA, heterogenous, Psoriatic arthritis | PSORIATIC ARTHRITIS, INFLAMMATORY DISEASE | Psoriatic arthritis (PsA) is a heterogenous and chronic systemic inflammatory disease that can manifest in multiple domains [Guselkumab is a high-affinity, fully human, monoclonal antibody that targets the IL-23p19 subunit [Previous analyses have shown that C-reactive protein (CRP) and type 17 effector cytokine serum levels are elevated in patients with PsA and can be reduced by inhibiting the IL-23p19 subunit or the IL-12/23p40 subunit [ | PMC10428525 |
Methods | PMC10428525 | |||
Study design, participants, and endpoints | The study design and participant eligibility criteria for COSMOS have been previously described [ | PMC10428525 | ||
Clinical assessments | DISEASE, DISEASE | Among participants in the biomarker cohort, baseline disease activity was evaluated using SJC, TJC, 28-joint Disease Activity Score using CRP (DAS28-CRP) [ | PMC10428525 | |
Biomarker sample collection | PsA, psoriasis | SEPARATION, PSORIASIS, INFLAMMATION | In COSMOS, blood samples for biomarker analyses were collected from all participants at Weeks 0, 4, 16, 24, and 48 into standard serum separation tubes. After 30 min, serum was separated via centrifugation at room temperature (15–20 min at 1500 × Serum samples from 24 healthy control volunteers (defined as those with no signs of active inflammation, PsA, or psoriasis based on physical assessment, medical history, and current medication) were also assessed for biomarkers. These samples were procured independently from a third party (Bioreclamation, Westbury, NY; Biological Specialty Corp., Colmar, PA). | PMC10428525 |
Biomarker analyses | tumor necrosis | INFLAMMATION, ADHESION, TUMOR NECROSIS | Serum samples for biomarker analyses were analyzed using qualified antibody-based assays. Serum concentrations of the T helper 17 (Th17) effector cytokine IL-17A were analyzed using Simoa™ single molecule array technology (Quanterix Corp., Billerica, MA), and those of IL-17F and IL-22 were analyzed using the Single Molecule Counting SMCxPRO Immunoassay Platform (Millipore, Burlington, MA). Acute phase proteins and markers of inflammation, CRP, serum amyloid A (SAA), IL-6, IL-10, interferon γ (IFNγ), tumor necrosis factor α (TNFα), soluble intercellular adhesion molecule-1 (sICAM), and vascular cell adhesion molecule (sVCAM), were analyzed using the Meso Scale Discovery Platform (Meso Scale Diagnostics, Rockville, MD). | PMC10428525 |
Statistical analysis | This analysis included participants with available baseline values and follow-up biomarker and clinical data over time. All analyses were post hoc; thus, reported | PMC10428525 | ||
Analysis of treatment effect on clinical efficacy | Differences in efficacy outcomes evaluated in the COSMOS biomarker cohort with guselkumab versus placebo treatment were assessed using a Chi-square test (categorical outcomes) or ANOVA (continuous measures). | PMC10428525 | ||
Analysis of baseline serum biomarker levels and correlation with disease activity | PsA | REGRESSION, DISEASE | Differences in baseline serum cytokine levels between participants with PsA and healthy controls were assessed using log2-transformed data with a general linear model. Serum protein expression levels were log2-transformed to normalize the data distribution. Differences of ≥ 1.4-fold with Correlations between baseline serum biomarker levels and baseline disease activity (i.e., DAPSA scores, PASDAS, and PASI scores) were assessed using Spearman linear regression, with a Spearman correlation ( | PMC10428525 |
Analysis of treatment effect on biomarker levels | For the evaluation of treatment effects (pharmacodynamic responses), changes in biomarker levels were compared between the active treatment and placebo groups. A contrast dataset for within-participant changes in biomarkers was generated from log2-transformed data, with the difference between the time point and baseline calculated for each participant and time point (Week 4, 16, 24, and 48). Differences were considered significant if they were ≥ 1.4-fold with a | PMC10428525 | ||
Analysis of association between biomarker levels and clinical response | Differences in baseline biomarker levels by clinical response at Week 24 (i.e., response versus nonresponse for ACR20/50, IGA 0/1, and PASI75) were evaluated using general linear model analyses and log2-transformed biomarker levels. Clinical response categorical variable was set as the primary fixed factor. In determining response, participants with missing efficacy data were considered nonresponders (nonresponder imputation). To evaluate the significance of changes in biomarkers from baseline among clinical responders and nonresponders, levels were compared between the specified time point and baseline separately for each clinical response group using general linear model analyses. Visit was set as the primary fixed variable. | PMC10428525 | ||
Results | PMC10428525 | |||
COSMOS participants and COSMOS biomarker cohort | PsA | DISEASE CHARACTERISTIC | In COSMOS, 189 participants with active TNFi-IR PsA were randomized to receive guselkumab Q8W, and 96 participants were randomized to receive placebo followed by guselkumab. Of these, 100 and 50 participants, respectively, were included in the biomarker cohort. In the COSMOS biomarker cohort, 21/100 (21%) participants in the guselkumab Q8W arm and 24/50 (48%) participants in the placebo arm qualified for early escape at Week 16.Baseline demographics and disease characteristics were generally similar between the overall COSMOS population and the biomarker cohort (Supplementary Table | PMC10428525 |
Clinical efficacy in the COSMOS biomarker cohort | Among participants in the biomarker cohort, 44% in the guselkumab group versus 20% in the placebo group achieved an ACR20 response at Week 24 ( | PMC10428525 | ||
Biomarker analyses | PMC10428525 | |||
Baseline serum levels and correlation with baseline disease activity | PsA, tumor necrosis, Psoriasis, psoriasis, PsO | TUMOR NECROSIS, PSORIASIS, PSORIASIS, PSORIATIC ARTHRITIS, ADHESION, PSORIATIC ARTHRITIS, DISEASE | Baseline serum concentrations of IL-6, IL-10, IL-17A, IL-17F, IL-22, TNFα, and IFNγ were significantly higher in the COSMOS biomarker cohort compared with healthy controls (Fig. Baseline levels of serum cytokines (IL-10, TNFα, and IFNγ), Th17 effector cytokines (IL-17A, IL-17F, and IL-22) and acute phase proteins (CRP, SAA, and IL-6) in participants with TNFi-IR PsA from COSMOS and in healthy controls.
Correlation of baseline cytokine biomarker levels with baseline clinical activity measures in participants with TNFi-IR PsA in the COSMOS biomarker cohortStatistics based on Spearman linear regressionBolded text highlights significant correlation between biomarker and clinical activity (BSA, body surface area; CRP, C-reactive protein; DAPSA, Disease Activity index for Psoriatic Arthritis; DAS28-CRP, 28- Disease Activity Score with C-reactive protein; IL, interleukin; PASDAS, Psoriatic Arthritis Disease Activity Score; PASI, Psoriasis Area and Severity Index; PsA, psoriatic arthritis; PsO, psoriasis; SAA, serum amyloid A; sICAM, soluble intercellular adhesion molecule-1; SJC, swollen joint count; sVCAM, soluble vascular cell adhesion molecule; TJC, tender joint count; TNF, tumor necrosis factor; TNFi-IR, tumor necrosis factor inhibitor-inadequate response | PMC10428525 |
Effect of treatment on biomarker levels | PsA | In participants randomized to guselkumab, reductions from baseline in levels of the Th17 effector cytokines IL-17A, IL-17F, and IL-22 and the acute phase proteins IL-6, CRP, and SAA were observed, while changes from baseline were not apparent in those who received placebo (Fig. Serum levels of IL-17A, IL-17F, IL-22, CRP, SAA, and IL-6 in participants with TNFi-IR PsA from COSMOS compared with healthy controls over time. Participants randomized to placebo crossed over to guselkumab at Week 16 (early escape; dotted line; | PMC10428525 | |
Biomarker levels and clinical response | PsA | Participants in the guselkumab group, but not the placebo group, who achieved an ACR20 response at Week 24 exhibited higher baseline IL-22 and IFNγ levels compared with ACR20 nonresponders (Fig. Baseline serum cytokine levels and clinical response at Week 24 in participants with TNFi-IR PsA from COSMOS by ACR20 response or IGA 0/1 response and change from baseline in serum IL-6 level by ACR20 or IGA 0/1 response over time. (Participants in the guselkumab group who achieved an ACR20 response at Week 24 exhibited a significantly greater reduction in IL-6 level from baseline at Week 4 compared with ACR20 nonresponders (Fig. | PMC10428525 | |
Discussion | PsA, skin disease, PsA disease, PsA. | DISORDER, SKIN DISEASE, DISEASE, JOINT DISEASE, PATHOGENESIS | These results provide further support for the important role of the IL-23/IL-17 pathway in PsA pathogenesis and expand our knowledge of guselkumab pharmacodynamic effects in patients with TNFi-IR PsA. Baseline levels of IL-6, IL-10, IL-17A, IL-17F, IL-22, TNFα, and IFNγ were higher in participants with TNFi-IR PsA compared with healthy controls. These findings were generally consistent with results from an exploratory biomarker analysis [This study further demonstrates serum biomarker levels are likely associated with disease activity assessed using PsA-specific composite indices. For example, CRP levels positively correlated with PASDAS, which includes CRP level as a component. Further, IL-6, SAA, and IL-17A levels showed a trend towards correlation with PASDAS, suggesting their important roles in PsA disease activity. Also of note, a correlation between CRP and DAPSA was not observed despite DAPSA including CRP as a measure; the reason for this is unclear. In both the prior and current studies, the association between the serum biomarkers analyzed and SJC or TJC was limited and may indicate that tissue-specific variations in cytokine levels and/or other systemic factors also play a role in this complex disorder. Similar results were seen in analyses from the two phase 3 PSUMMIT studies of ustekinumab, which reported that serum levels of IL-23, IL-17A, and IL-17F correlated with baseline skin disease in participants with PsA, but did not find a clear association of these cytokines with joint disease [Similar to the DISCOVER-1 and -2 biomarker results in participants who were mostly biologic-naïve [Similar exploratory analyses have been performed in clinical studies with other classes of PsA treatments, including TNFi, IL-17i, and Janus kinase inhibitors [Results of analyses reported herein are limited by the potential incongruence between serum and tissue (e.g., joint and skin) levels of cytokines and acute phase proteins. While analysis of serum levels allows for collection of serial samples in the clinic, evaluation of tissue would further our knowledge of disease pathogenesis and could potentially help further elucidate the mechanism(s) of action of guselkumab in joints, as preclinical evidence suggests that IL-17 is a key mediator of PsA joint pathogenesis [We have now consistently observed correlations between serum biomarker levels and PsA disease activity in the DISCOVER-1 and -2 and COSMOS trials that reinforce the important role of serum inflammatory factors and cytokines in PsA pathogenesis. Additional research is needed to confirm these findings in a TNFi-IR population and more fully contrast with bio-naïve PsA patients. Further research will also be needed to strengthen the potential of using serum inflammatory biomarker levels to guide therapeutic selection for patients with PsA. | PMC10428525 |
Conclusions | Overall, these data suggest that guselkumab reduces the levels of key effector inflammatory cytokines, including those associated with the IL-23/IL-17 pathway, at early time points in participants with TNFi-IR PsA. Reductions were generally sustained through Week 48, with levels of IL-17F, IL-22, CRP, and SAA approximating those observed in healthy controls. Higher baseline levels of certain cytokines and acute phase reactants were observed in ACR20 (IL-22 and IFNγ) and IGA 0/1 (SAA, IFNγ, and IL-17A) responders than in nonresponders at Week 24. The clinical utility and treatment implications of these findings require further investigation. | PMC10428525 | ||
Acknowledgements | Medical writing support was provided by Bret Fulton, RPh, and Jeanne McKeon, PhD, of Lumanity Communications Inc., under the direction of the authors in accordance with Good Publication Practice guidelines ( | PMC10428525 | ||
Authors’ contributions | GS | GS, SG, SDC, and MShawi contributed to the conception and/or design of the work and data interpretation. WC contributed to the conception and/or design of the work and data analysis and interpretation. FL, MZ, MSharaf, LCC, and SS contributed to data interpretation. All authors contributed to drafting and/or substantively revising the manuscript and gave final approval for submission. | PMC10428525 | |
Funding | This study was sponsored by Janssen Research & Development, LLC, Spring House, PA, USA. | PMC10428525 | ||
Availability of data and materials | Johnson & Johnson is | The data sharing policy of Janssen Pharmaceutical Companies of Johnson & Johnson is available at | PMC10428525 | |
Declarations | PMC10428525 | |||
Ethics approval and consent to participate | The governing ethical bodies for each of the 84 participating sites approved the COSMOS trial protocol. | PMC10428525 | ||
Consent for publication | Not applicable. | PMC10428525 | ||
Competing interests | Johnson & Johnson, of which Janssen, Johnson & Johnson., Johnson & Johnson MEA | GS has received speaker fees from AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Gilead, Janssen, Novartis, and UCB.WC and SG are employees of Janssen Research & Development, LLC, and own stock or stock options in Johnson & Johnson, of which Janssen Research & Development, LLC is a wholly owned subsidiary.SDC is an employee of Janssen Scientific Affairs, LLC, and owns stock or stock options in Johnson & Johnson, of which Janssen Scientific Affairs, LLC is a wholly owned subsidiary.MShawi is an employee of Immunology Global Medical Affairs, Janssen Pharmaceutical Companies, a wholly owned subsidiary of Johnson & Johnson, and owns stocks in Johnson & Johnson.FL is an employee of Immunology Global Medical Affairs, Janssen Pharmaceutical Companies, a wholly owned subsidiary of Johnson & Johnson, and owns stock in Johnson & Johnson.MZ is an employee of Janssen Medical Affairs, LLC, and owns stock or stock options in Johnson & Johnson, of which Janssen Medical Affairs, LLC, is a wholly owned subsidiary.MSharaf is an employee of Johnson & Johnson MEA and owns stock or stock options in Johnson & Johnson.LCC has received consultant fees from AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, MoonLake, Novartis, Pfizer, and UCB; grant/research support from AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB; and speaker fees from AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Medac, Novartis, Pfizer, and UCB.SS has received institutional research grants from AbbVie, Amgen (previously Celgene), Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Janssen, and UCB; and speaker fees from AbbVie, Amgen, Biogen, Eli Lilly, GlaxoSmithKline, Janssen, and UCB. | PMC10428525 | |
References | PMC10428525 | |||
Introduction | Cervical cancer | CERVICAL CANCER, SECONDARY, CERVICAL CANCER | Cervical cancer (CC) rates are high in Uganda, yet CC screening rates are very low. Our peer advocacy group intervention, Game Changers for Cervical Cancer Prevention (GC-CCP), was shown to increase CC screening uptake among social network members. In this secondary analysis, we examined mediators and moderators of this effect to better understand how and for whom the intervention was most successful in promoting CC screening. | PMC10173559 |
Methods | REGRESSION | We conducted a pilot randomized controlled trial of GC-CCP in Namayingo district, Eastern Uganda between September 2021 and April 2022. Forty adult women who had screened for CC in the past year (index participants) enrolled at baseline: 20 were randomized to receive the 7-session intervention to empower women to engage in CC prevention advocacy, and 20 were assigned to the waitlist control; from these index participants, 103 unscreened social network members (alters) also enrolled. All participants were assessed at baseline and month 6 follow-up. Change in cognitive and behavioral CC-related constructs from baseline to month 6 were examined as mediators, using multivariate linear regression analysis. Index and alter demographics and index CC treatment status were examined as moderators. | PMC10173559 | |
Results | pre-cancerous lesions | Increased alter engagement in CC prevention advocacy fully mediated the intervention effect on alter uptake of CC screening, and was associated with an increased likelihood of alter CC screening. CC treatment status of the index participant was the sole moderator of the intervention effect, as those in the intervention group who had screened positive and received treatment for pre-cancerous lesions were more likely to have alters who got screened for CC by month 6. | PMC10173559 | |
Conclusion | The effect of GC-CCP on alter CC screening is greater when the alter reports increased engagement in her own advocacy for CC prevention with others. The intervention effects on increased engagement in CC prevention advocacy among both index and alter participants suggest a diffusion of advocacy, which bodes well for dissemination of knowledge and screening activation throughout a network and the larger community. | PMC10173559 | ||
Keywords | PMC10173559 | |||
Introduction | INVASIVE CANCER, PRECANCEROUS LESIONS, CERVICAL CANCER | The World Health Organization (WHO) estimates that implementation of cost-effective and evidence-based interventions, including human papillomavirus (HPV) vaccination of girls, screening and treatment of precancerous lesions, and improving access to diagnosis and treatment of invasive cancers will reduce the median cervical cancer (CC) incidence rate by 97% by 2120– averting more than 74 million new cases of cervical cancer between 2020 and 2120 [Several interventions have been implemented to increase early detection of CC among women globally, including health education interventions [
Conceptual framework for promotion of cervical cancer (CC) prevention advocacy among screened women to affect CC screening among social network membersWe conducted a pilot randomized controlled trial of GC-CCP and found that the intervention led to increased engagement in CC prevention advocacy, and uptake of CC screening in over half of the previously unscreened women in the social networks of the intervention group, compared to less than one-fifth of their counterparts in the control group (Wagner et al., | PMC10173559 | |
Methods | PMC10173559 | |||
Study setting | cancer, Cancer | CANCER, CANCER | This analysis uses data collected as part of a randomized control trial of GC-CCP in Eastern Uganda between September 2021 and April 2022. The pilot study was conducted at Buyinja Health Center IV and Banda Health Center III in Namayingo, a rural community in the Busoga region of Uganda. The selection of the study site was influenced by previous work in this area by our partner institution (Rays of Hope Hospice Jinja; RHHJ) coupled with low CC screening rates observed among women in this district. CC screening with visual inspection (VIA) and thermal therapy are available at both Buyinja and Banda health centers, and from RHHJ which conducts periodic mobile CC screening and thermal therapy “day camps”. Women who need biopsies are sent to Jinja (approximately 90 km from Namayingo), and if cancerous lesions are present, they are referred to the Uganda Cancer Institute, the leading tertiary public cancer care centre located in Kampala. | PMC10173559 |
Study design | The study design has been described in detail in our previous publication [ | PMC10173559 | ||
Participants | pre-cancerous or cancerous lesions | DISEASE, RECRUITMENT | Index participants were enrolled into the study if they were aged 18 years or older, had screened for CC within the past year, had stable health status (i.e., not in end stages of disease, so that they were likely to complete the 6-month study follow-up), and had shared their CC screening experience with at least one woman (alter) who they perceived to not have screened for CC in the past 3 years. Alter participants were eligible if they were at least 18 years of age, were recruited by a woman who was enrolled as an index participant, and self-reported not being screened for CC in the past 3 years. All participants had to speak either Samia or Lusoga, the two prominent languages in Namayingo district.Recruitment of index participants was purposive in order to recruit a balance of women who screened positive for signs of CC risk (pre-cancerous or cancerous lesions), and women who screened negative, so that we could assess whether this factor was associated with the outcomes measure of engagement in CC prevention advocacy. Candidates for index participation were informed of the study by health care providers and those who expressed interest were referred to the study coordinator for confirmation of eligibility and consent procedures. Women who decided to enroll were administered the baseline survey, which included listing up to 12 women in their social network. To recruit alters, we randomly selected five alters who the index participant reported as knowing her CC screening experience (or as many as there were if less than five); the index participant was then asked if she was comfortable asking three of these alters to participate. The index participant was asked to call each selected alter at the end of the interview to describe the study in the presence of the coordinator, who then scheduled a study visit if the alter expressed interest in participating. If an alter refused or could not be reached, a replacement was randomly selected from the list of alters who knew the index participant’s CC screening experience (and whom the index participant was comfortable recruiting). When screening the alter, the coordinator confirmed that the individual was not already recruited by another index. All participants provided written informed consent. | PMC10173559 |
Intervention | The intervention has been described previously [The sessions were conducted using a structured facilitator manual, in the predominant local languages of Samia and Lusoga, by two peer facilitators from Namayingo who themselves had been screened for CC. The facilitators were trained by the senior investigators over three days. The supervisor of the facilitators observed the implementation of each session and provided feedback and further training as needed during weekly supervision. | PMC10173559 | ||
Measures | Assessments included a standard survey (index and alter participants) and social network assessment (index participant only), which were administered in either Samia or Lusoga (depending on the preference of the participant) using Network Canvas computer-assisted software. Each measure was assessed with both index and alter participants, unless otherwise noted. Measures were translated using standard translation/backtranslation methodology. CC screening and treatment utilization were verified with abstracted medical chart data. All measures were developed by the study team, except those in which an attribution is cited. For measures developed by the study team that included at least three items, we cite internal reliability statistics (Cronbach’s alpha). | PMC10173559 | ||
CC screening and treatment | cancerous lesions, pre-cancerous lesions, pre-cancerous | Data were collected to determine if the participant had ever been screened for CC using visual inspection using acetic acid (VIA) or pap smear, and if so, when. For participants who had been screened, it was determined if the screening resulted in pre-cancerous lesions or potential cancerous lesions, in separate items; if either type of lesion was reported, receipt of corresponding procedure or treatment (cryotherapy or thermal therapy for pre-cancerous; biopsy to confirm diagnosis, and radiation, chemotherapy or surgery treatment for cancerous) was assessed. | PMC10173559 | |
Potential mediators | The following measures were assessed as potential mediators of the effects of intervention effect on alter CC screening, as each was targeted by the components of the intervention. | PMC10173559 | ||
Potential moderators | SECONDARY | The variables we examined as potential moderators among both index and alter participants consisted of age and any secondary education, in addition to CC-related treatment history (index participants only) and presence of a main sex partner (alter participants only). | PMC10173559 | |
Data analysis | REGRESSION, SECONDARY | Descriptive and bivariate (2-tailed independent t-tests; chi-square or Fisher’s Exact tests) statistics were used to compare baseline sample characteristics of index and alter participants in the control versus intervention arms, in separate analyses. To examine intervention effects on index and alter measures of CC-related processes, we conducted multiple linear regression analyses. In each model, the month 6 measure of the outcome was the dependent variable, while independent variables included the baseline measure of the dependent variable and an indicator of study arm. If a measure was missing at month 6, the baseline measure of the variable was used to replace the missing value. Normal probability plots were constructed for each dependent variable and examined qualitatively for violation of normality. Similar multiple logistic regression models were run to examine whether alter uptake of CC screening by month 6 was associated with the index and alter measures of CC-related processes.Measures of index and alter CC-related processes (potential mediators) were examined as mediators of the intervention effect on alter uptake of CC screening if the measure was significantly associated with both the intervention and alter CC screening. To test for mediation, we employed Proc Causalmed (SAS v9.4), which uses bootstrap resampling to compute standard errors and confidence intervals for causal mediation effects and decompositions. A two-step approach was used to test each potential mediator separately. In step one, the dependent variable was alter uptake of CC screening by month 6, while independent variables consisted of an indicator of study arm and the baseline measure of the mediator. In step two, the month 6 measure of the mediator was added to the model, resulting in the model assessing the mediating effect of change in the mediator from baseline to month 6. Covariates included in each model consisted of age < 35 years, any secondary education, and presence of a main sex partner. We examined each potential mediator separately, because the mediators are conceptually inter-correlated, and testing multiple mediators simultaneously would complicate the interpretation of the models. To test for moderation of the intervention effect on alter CC screening, for each potential moderator we ran a logistic regression modeling alter CC screening at month 6 as the dependent variable. Independent variables included an indicator for study arm, the moderator measured at baseline, and their interaction. | PMC10173559 | |
Ethical considerations | The study protocol was reviewed and approved by the Makerere University School of Public Health Research and Ethics Committee, and the Uganda National Council for Science and Technology. | PMC10173559 | ||
Results | PMC10173559 | |||
Sample characteristics | SECONDARY | Of the 40 index participants, 57.5% were older than 35 years, 22.5% had any secondary education, 87.5% reported that they had a main sexual partner, 92.5% had children, and 7.5% were HIV-positive. There were no significant differences between the index participants randomized to the intervention and those that were randomized to the control arm. Among the 103 alter participants, 37.9% were older than 35 years of age, 29.1% had any secondary education, 81.6% reported that they had a main sexual partner, 95.1% had children, and 5.8% were HIV-positive. Compared to alters of index participants in the control arm, alters of index participants in the intervention arm were significantly more likely to have any secondary education (39.7% vs. 15.6%; p = 0.01) and to report that they had a main sex partner (89.7% vs. 71.1%; p = 0.02). | PMC10173559 | |
Mediation of the intervention effect on alter CC screening by index participant measures | SE | REGRESSION, CERVICAL CANCER, SECONDARY | Table
Bivariate and multivariate correlates of cervical cancer (CC) screening among alters* Bivariate analysis was conducted using 2-tailed independent t-tests. Multiple logistic regression models of alter uptake of CC screening included the month 6 measure of alter CC screening as the dependent variable, and the month 6 and baseline measures of the predictor as independent variablesOR = odds ration; CI = confidence intervalTable
Logistic regression models examining index measures at month-6 as mediators of intervention effect on alter cervical cancer (CC) screening
3.72(0.13, 109.20)
7.78(0.71, 85.32)
0.98(0.92, 1.04)1.02(0.47, 2.18)
1.53(0.80, 2.92)A two-step approach was used to test each potential mediator separately. In step one (“without mediator column”), the dependent variable was alter uptake of CC screening by month 6, while independent variables consisted of an indicator of study arm and the baseline measure of the mediator. In step two (“with mediator column”), the month 6 measure of the mediator was added to the model. Covariates included in each model consisted of age < 35 years, any secondary education, and presence of a main sex partnerOR = odds ratio; CI = confidence interval; bsln = baseline; M6 = month-6 follow-up visitWith index participant measures of CC knowledge, sharing of CC screening experience, engagement in CC prevention advocacy, and CC screening advocacy across all named alters each being associated with both the intervention and alter CC screening, we then conducted mediation analysis to assess whether each mediated the intervention effect on alter CC screening, in separate logistic regression models. None of the variables were found to mediate the intervention effect (see Table
Linear regression models of intervention effects on alter cervical cancer (CC)-related processes (mediators) at month 6, controlling for baseline measure of the mediator* p values from bivariate comparisons using independent 2-tailed t-testsBeta coefficients and standard errors (SE) are from multiple linear regression models of alter CC-related at month 6 as the dependent variable, and independent variables consisting of intervention condition and the baseline measure of the CC-related process | PMC10173559 |
Mediation of the intervention effect on alter CC screening by alter participant measures | SE | REGRESSION, CERVICAL CANCER, SECONDARY | The first step to identifying potential mediators of the intervention effect on alter CC screening was to identify variables that were associated with the intervention as well as alter CC screening. Starting with alter participant measures, Table
Linear regression models of intervention effects on index cervical cancer (CC)-related processes (mediators) at month 6, controlling for baseline measure of the mediator* p values from bivariate comparisons using independent 2-tailed t-testsBeta coefficients and standard errors (SE) are from multiple linear regression models of index CC-related at month 6 as the dependent variable, and independent variables consisting of intervention condition and the baseline measure of the CC-related processTable With alter measures of CC knowledge, CC risk management self-efficacy, and engagement in CC prevention advocacy each being associated with both the intervention and alter CC screening, we then conducted mediation analysis to assess whether each measure mediated the intervention effect on alter CC screening, in separate logistic regression models. Change in alter engagement in CC prevention advocacy from baseline to month 6 fully mediated the intervention effect on alter CC screening (see Table
Logistic regression models examining alter measures at month-6 as mediators of intervention effect on alter cervical cancer (CC) screening
A two-step approach was used to test each potential mediator separately. In step one (“without mediator column”), the dependent variable was alter uptake of CC screening by month 6, while independent variables consisted of an indicator of study arm and the baseline measure of the mediator. In step two (“with mediator column”), the month 6 measure of the mediator was added to the model. Covariates included in each model consisted of age < 35 years, any secondary education, and presence of a main sex partnerOR = odds ratio; CI = confidence interval; bsln = baseline; M6 = month-6 follow-up visit | PMC10173559 |
Moderators of the intervention effect on alter CC screening | precancerous lesions | REGRESSION, PRECANCEROUS LESIONS | In regression models examining moderation, receipt of thermal therapy for precancerous lesions by index participants was the only significant moderator of the intervention effect on alter CC screening [Adj. OR (95% CI) = 21.08 (1.78, 249.82)]. Figure
Moderating effects of index participant’s CC-related treatment status on the intervention effect on alter CC screening | PMC10173559 |
Discussion | pre-cancerous lesions | RECRUITMENT | Prior analysis of the study data revealed an effect of the GC-CCP intervention on increased CC screening uptake among previously unscreened social network members (alters) (15). In the analysis reported here, we sought to understand how the intervention achieved this effect, and for whom the intervention was most successful, by examining mediators and moderators of the intervention effect on alter CC screening. The most direct effect of the intervention was engagement in CC prevention advocacy among intervention recipients (index participants); therefore, our hypothesis was that CC prevention advocacy conducted by the index participants would mediate the intervention effect on increased CC screening uptake among alters. Yet, while there was an intervention effect on increased CC prevention advocacy among index participants (Wagner et al. The GC-CCP intervention had effects on many of the constructs that compose the conceptual framework that guided the development of the intervention (see Fig. The mediating effect of increased alter engagement in CC prevention advocacy, as opposed to index engagement in advocacy, perhaps should not be surprising. The increase in alter engagement in advocacy is arguably a result of the alters being targeted with advocacy by the index participants. Furthermore, the finding that engagement in CC prevention advocacy also increased among alter participants suggests a diffusion of advocacy created by the intervention. This is particularly promising, as network-based peer advocacy interventions such as GC-CCP are designed to disseminate knowledge, motivation and self-efficacy for health behavior through diffusion of advocacy [The only variable found to moderate the intervention effect on alter CC screening was CC treatment status of the index participants. Index participants in the intervention group who had screened positive and been treated for pre-cancerous lesions were more likely to have alter participants who got screened for CC during the study follow-up period. This finding suggests that women who screen positive may be more motivated to engage in CC prevention advocacy, and they may also receive more information about CC during the process of receiving treatment, both of which encourage them to engage in more advocacy. This is consistent with our prior analysis of baseline data that showed index participant engagement in CC prevention advocacy was positively correlated with having received CC-related treatment (Wagner et al., There are several limitations to our analysis. A selection bias was likely present in the recruitment of the index participants, as they had decided to enroll in a study that would train them to engage in CC prevention advocacy; motivation to be such an advocate is likely associated with greater CC knowledge and other constructs we measured, and not representative of the general population of women who had recently screened for CC. Similarly, there was a selection bias related to the alter participants, as index participants needed to be comfortable recruiting these alters; these alters may not be representative of all women in the social networks of the index participants. Validated measures or measures used by other research groups were not available for most constructs, resulting in the need for our team to develop many of the measures used. Internal reliability statistics were moderate or good for most of these measures, but further psychometric evaluation is needed in future studies. Other limitations include the small sample size and limited statistical power. | PMC10173559 |
Conclusion | Our study shows that the benefits of GC-CCP on alter uptake of CC screening are enhanced by the recipient of advocacy increasing her own advocacy for CC prevention and screening. The GC-CCP intervention had strong effects on nearly all components of the intervention, including index participants’ engagement in prevention advocacy. However, it was the alters’ engagement in prevention advocacy themselves that fully mediated the effect of the intervention on alter screening. The intervention effects on increased engagement in CC prevention advocacy and CC knowledge, among both index and alter participants, suggest a potential diffusion of advocacy and CC information throughout the network, which bodes well for CC screening activation throughout the network and the larger community. | PMC10173559 | ||
Acknowledgements | We acknowledge support from the staff of Buyinja Health Center IV and Banda Health Center III and the Study Coordinator (Grace Namisi) during the implementation of the GC-CC prevention advocacy intervention; and study participants for participating in this study. | PMC10173559 | ||
Authors’ contributions | G.W. conceived the study and led the analysis of data. J.K.B.M. supervised data collection, provided scientific oversight during the implementation of the intervention and drafted the manuscript. G.W., J.K.B.M. and R.K.W. supported the interpretation of study findings. N.E., M.J., S.N., K.B., L.E., and R.K.W. guided the initial conceptualization of the study, provided scientific oversight during study implementation, and reviewed the final manuscript for substantial intellectual content. All authors read and approved the final manuscript. | PMC10173559 | ||
Funding | This research is funded by a grant from the US National Institutes of Health/Fogarty International Center (R21TW011728; PI: Wanyenze). | PMC10173559 |
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