Population-based self-sampling under primary care conditions – a possible approach for cervical cancer screening in Indonesia (IndoCerCa study)

Population-based self-sampling under primary care conditions – a possible approach for cervical cancer screening in Indonesia (IndoCerCa study) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Population-based self-sampling under primary care conditions – a possible approach for cervical cancer screening in Indonesia (IndoCerCa study) Supriyatiningsih Wenang, Dianita Sugiyo, Sutantri Sutantri, Lidia Febrianti, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7429458/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Introduction : In LMIC cervical cancer is a major burden. Screening is mainly based on visual inspection lacking sufficient sensitivity and specificity. For roll-out of colposcopy-based early detection sufficient qualified staff is not available. Several self-sampling device products have been proposed as alternative, but their usability in primary care needs to be proven. Implementation of an HPV-based self-sampling approach in a population-based setting in Indonesia was evaluated. Methods : Four self-sampling devices (2 urine, 2 swab) were applied in a primary care setting covering an entire district in Indonesia with Kulon Progo as pilot region. Cluster randomization was used for comparison of rural and urban areas. HPV-testing was done using standardized and validated PCR-techniques. HPV-positive women and a randomly selected HPV-negative control group underwent colposcopy, PAP smears and biopsies for CIN validation. Results : In 21 primary care units 2056 women (30-55 y) were recruited. Three devices achieved sufficient technical validation (92.1 – 99.7% DNA detection rate). Participant’s test acceptance was 99.1%. HPV-prevalence was 2.6% (urine 2.4%, swab 2.8%). In 29.4% of HPV-positive women high-risk HPV-16/18 were detected. Colposcopy and morphological examination were refused by 3.0% of HPV-positive women and were technically invalid in 5.0%. Pathology revealed NILM in 55.8%, CIN I in 25.0% and CIN II+ in 3.8%. In the control group CIN I was found in 2.0%. This resulted in sensitivity for all CIN/CIN II+ of 27,4%/100,0%, specificity of 98,5%/97,7% with negative (NPV: 97,9%/100,0%) and positive predictive values (PPV: 34,1%/4,5%). Regression analysis confirmed high negative predictive impact of HPV-negativity in women >40 years. Conclusions : Under primary care setting self-sampling-based HPV-testing is accepted. Urine- and swab-based techniques can be applied if the test systems provide technically valid DNA-detection rates. The prevalence was very low and requires further comparison within Indonesia. High NPV of this approach supports its applicability as screening in LMICs. For high-risk lesions PPV is still low suggesting a combination with additional test that are mainly independent from the availability of qualified staff. Screening human papilloma virus cervical cancer self-sampling prevalence Figures Figure 1 Figure 2 Introduction The public health challenge of cervical cancer continues to be significant, especially in low- and middle-income countries (LMICs). Globally, it is the fourth most common cancer among women, with approximately 660,000 new cases and 350,000 deaths reported in 2022. The early detection of cervical cancer in Indonesia is crucial due to its leading cause among cancer-related deaths in women, highlighting the critical importance of implementing effective screening methods. Human Papillomavirus (HPV) infection is the primary cause of cervical cancer, with high-risk HPV (HR-HPV) types leading to cervical intraepithelial neoplasia (CIN) and invasive cervical cancer. Effective screening relies on two critical metrics: sensitivity (the ability to identify those with the disease correctly) and specificity (the ability to properly identify those without the disease). The current population-based approach in Indonesia using visual inspection (VIA) suffers severely from related shortcomings and low rates of predictive accuracy. Understanding HR-HPV prevalence across Asia is crucial for targeted prevention and treatment strategies. For example, in Malaysia HR-HPV prevalence is 4.53% with HPV16/18 at 1.23% and other high-risk types at 3.30%. In contrast, for China HR-HPV prevalence has been reported as 9.9% with HPV16/18 at 2.4% and other high-risk types at 7.5% and among women aged 30–64 as 14.4% and 4.7%, respectively. In Hong Kong, HR-HPV prevalence is 8.75%, with HPV16 in 1.15% and HPV18 in 0.61% of women. In Korea, HR-HPV prevalence ranges from 8.02–11.45%, with HPV52 notably high at 17.26%. In Thailand, HR-HPV prevalence is 5.6%, with HPV16/18 at 1.7%. Another Thai study reported prevalence of abnormal cervical cytology rates of 4.8% with conventional Pap smears and 5.7% with liquid-based Pap smears (LBP). Within the Asian environment, primary HPV testing appears to be more effective than cytology-based methods for detecting CIN2 + lesions. In China, primary HPV testing showed a significantly higher sensitivity for detecting CIN2 + than cytology. 7 Similarly, in Hong Kong, Korea and other Asian investigations, HPV-DNA detection exhibited high sensitivity and specificity. 8, 9, 11, HPV primary screening with more advanced cytology diagnostics, such as p16/Ki-67 dual stain, showed higher sensitivity for CIN2 + detection than conventional Pap smears. 10, However, all these high performance screening approaches suffer from implementation barriers, especially in LMICs mainly due to economic restrictions, insufficient availability of qualified personnel or lack of acceptance within the target population. Effective screening can significantly reduce cervical cancer mortality rates. HPV self-sampling allows women to collect samples at home and can increase screening coverage and early diagnosis. Self-sampling is available using swab- or urine based collection. These obtained specimens need to be processed properly to obtain valid results. Automated systems for HPV-DNA detection can subsequently reduce technical failure and insufficient detection rates. However, challenges, such as limited national insurance reimbursements, government regulations, lack of clinician awareness, and limited availability of HPV-DNA testing in Indonesia must be addressed for a potential roll-out. Cultural barriers, including fear, shyness, and anxiety about screening procedures and results, also impact participation 14 and need to be evaluated. For a national roll-out, especially in a country with relevant access barriers, such as due to remote and rural population, these screening approaches need to work under primary care conditions. Therefore, we investigated the usability of different self-sampling devices for HPV-DNA detection under primary care condition covering an entire district in Indonesia. This was combined with the development of a training program for the involved midwifes as blue-print for subsequent potential roll-out. Technical and clinical test performance were combined with an evaluation of acceptance barriers. Methods Study design Target population Primary care setting was applied by conducting self-sampling in primary care units (Puskesmas) in the district of Kulon Progo, Yogyakarta Province, Indonesia. All of these puskesmas were randomly assigned to one of the self-sampling devices with stratification according to rural/urban and urine/swab distribution. (Suppl. Table 1) According to the legal Indonesian framework all puskesmas can be attributed regarding the covered region and population. This provided a distinction between rural (n = 13) and urban (n = 8) recruitment areas enabling a cluster randomization for the usage of the self-sampling devices (urine n = 10, swab n = 11). Invitations for study participation were send to randomly selected women within each puskesmas coverage population in the respective age by the local Ministry of Health (MoH). This ensured participation also for women in remote areas. Traveling costs related to study participation were reimbursed. Women were eligible in an age of 30–55 years, non-pregnant without history of cancer. 100 participants per involved puskesmas were targeted, thus an overall recruitment of 2.100 women. Acceptance evaluation In addition to the self-sampling, the participants were asked to fill-out a validated acceptance questionnaire. This questionnaire contained 26 questions with overall 130 subitems covering the domains health/cancer literacy, cancer prevention knowledge, coping strategies, acceptance of cervical cancer screening. In addition, demographic data (age, education, social environment) were obtained. If applicable, equidistant rating scales were applied and the validation was done involving local midwifes and volunteer laypersons. Ethical approval was given by the Gadjah Mada University (KE/FK/1445/EC). Informed consent was obtained by all participants before recruitment into the study. Registration was not required due to the non-interventional and observational character of the investigation. Diagnostic algorithm Self-sampling Prior to recruitment all involved midwifes in the participating puskesmas were trained regarding the handling of the self-sampling devices and informed consent procedures. Written and video-clip explanatory material about the device handling was provided for the recruited women before self-sampling. Midwifes were allowed to support the women in handling and all samples were obtained within the primary care units (home-based self-sampling was excluded). The following devices were used in the study group I: UriSponge™ (Copan®); group II: Viba Brush® (Rovers®); group III: Colli-Pee 10 mL UCM (Novosanis®); group IV: MSwab® 6E067N (Copan®). Storage and transportation of the samples to the central laboratory for testing was performed according to the manufactures’ instructions. HPV-detection Detection of HPV –DNA was done using the standard procedures of the Cobas® 4800 HPV system (Roche®). HPV-16, HPV-18 and other HPV-genotypes were differentiated. Prior to testing the lab staff was specifically trained and a technical pilot test phase was performed. This pilot investigation evaluated the entire pre-diagnostic chain and provided a technical validation based on 75 participants for each sampling device. Clinical validation All participating women were informed about their HPV-test results by the primary care structures. HPV-positive women were invited to colposcopy and further clinical evaluation. For evaluation of test results a randomly selected group of HPV-negative participants (similar number as for HPV-positive) was included in the clinical validation group. Full coverage of clinical validation for all participants could not been done due to resource limitations for colposcopy under the targeted real-life conditions. This clinical examination was conducted in a specialized center at Sardjito Hospital, a vertical hospital in Yogyakarta province within an advanced care hospital. It included colposcopy, PAP smear and a cervical biopsy. Reporting of the cytology and histology results was done according to international guidelines. CIN-positive women were subsequently treated based on the Indonesian national algorithms that are ruled by the respective MoH. Statistical analysis Test evaluation Prevalence of HPV-positivity and precancerous lesions was determined. Sensitivity, specificity and predictive values were calculated for the self-sampling approaches based on the clinical validation results and back-calculation of HPV-negative evaluation. Cross table comparison was done using Chi²-tests and, when appropriate, Pearson contingency coefficient and Cramer’s V were used. Multivariate analysis For multivariate analysis potential interactions between various variables werre addressed. Collinearity was assumed for variables with R > 0.8 in cross-correlations. ANOVA method was applied for univariate group comparison. Scheffé procedure and Bonferoni correction were done for multivariate analyses and related post-hoc tests. For logistic regression modelling all related variables in each test approach were evaluated using CIN-positivity or high risk CIN2 + as dependent target parameter. Age groups, rural/urban location, marriage status, educational level and HPV genotypes were tested as potential independent determinants. The obtained regression functions were evaluated based on the 2-fold log likelihood and Chi²-tests. Nagelkerke-R² was used to explain the variance of the regression model with values > 0.5 suggesting relevant determinants. All statistical analyses were performed using IBM SPSS Statistics Version 29. Results Technical validation of self-sampling devices In a first pilot group (n = 295) the technical performance of each self-sampling device was evaluated. In this group Colli-Pee and MSwab® showed 100% detection rates for human DNA, whereas Viba Brush® had valid testing in 76.5% and UriSponge™ in only 5.6% of the analyzed 36 participants. (Fig. 1 a) Therefore, the latter device was excluded from the subsequent evaluation and replaced by self-sampling using the second urine-based device (Colli-Pee). A second urine-based self-sampling was offered to all participants in this group. Performance of study cohort Overall, 2056 participants were recruited and 2020 women were included in the final evaluation. (Fig. 1 ) Using the three sampling devices, for 1958 participants technically valid HPV testing was obtained with final DNA detection rates of 92.1% for Viba Brush®, 99.4% for Colli-Pee and 99.7% for MSwab® (Table 1 ; Fig. 2 a). This association of the technical validity with the sampling devices was significant (p < 0.001). Age was not significantly different between urban (41.17 ± 6.52 years) and rural (40.80 ± 6.29 years) participants (p = 0.28). Detection of HPV-DNA HPV-DNA was detected in 51 cases reflecting 2.6% prevalence in the target population. This detection rate differed slightly, but not significantly between the sampling devices (2.3% − 2.9%) or the sampling method (urine: 2.4%; swab 2.8%). (Fig. 2 b) In 29.4% of the HPV-positive women high risk genotypes (HPV16/18) were detected. (Fig. 2 c) In two cases HPV16 infection was combined with other HPV genotypes. This genotype distribution was comparable for the devices or the sampling methods and also not significantly associated with applied technology. Table 1 Test results for HPV-DNA detection by self-sampling devices Group urine swab total Device UriSponge™ Colli-Pee UCM Total*** Viba Brush® MSwab® total # participants 36 947 947 456 599 1055 2002 Age (mean ± SD) 41.06 ± 6.30 41.06 ± 6.30 40.10 ± 6.90 41.18 ± 6.26 40.82 ± 6.50 40.94 ± 6.39 HPV16 0 1 1 2 2 4 5 HPV18 0 3 3 2 3 5 8 HPV other 1 18 19 7 10 17 36 HPV multiple* 0 0 0 1 1 2 2 Invalid** 34 6 6 36 2 38 44 Sum HPV positive 1 22 23 12 16 28 51 Sum HPV negative 1 918 918 408 581 989 1907 # HPV valid tests 2 941 941 420 597 1017 1958 Validity rate 5,6% 99,4% 92,1% 99,7% HPV positive rate 2,3% 2,4% 2,9% 2,7% 2,8% 2,6% * in both cases HPV16 & HPV others ** sufficient detection of human cytokeratin-DNA as positive control was not achieved *** The group of UriSponge™ was excluded in the final analysis Clinical validation Overall, for 100 women colposcopy combined with pap-smear cytology and cervical biopsy (histology) was suggested (51 HPV-positive, 49 HPV-negative). Two of the HPV-positive participants refused further clinical evaluation (refusal rate 2.0%). In 6/98 (5 HPV-positive, 1 HPV-negative) cases the pathological evaluation reported insufficient amounts of material that was classified as invalid colposcopy (6.1%). CIN-positive situations were confirmed in 16 of the evaluable participants (15/44 HPV-positive [34.1%], 1/48 HPV-negative [2.1%]) and two HPV-positive women showed high risk CIN2 + results [2/44; 4.5%; none HPV-negative]. (Fig. 2 d) For calculation of test performance, the randomly selected HPV-negative colposcopy group (including drop-out and invalid colposcopy rates) was projected towards the entire HPV-negative participants. These numbers were used to obtain sensitivity, specificity and predictive values (PPV, NPV) for self-sampling HPV-based screening. Table 2 contains these data for identification of CIN-positivity and for detection of the high-risk CIN2 + group. Overall, CIN-positivity can be assumed with a prevalence of 2.8% in the target population whereas only 0.1% are expected to have a high-risk CIN2 + cervical status. Due to this low prevalence a respective correction for pretest probability was not required. Table 2 All CIN positive CIN II+ Sensitivity 27,4% 100,0% Specificity 98,5% 97,7% Positive predictive value (PPV) 34,1% 4,5% Negative predictive value (NPV) 97,9% 100,0% CIN-prevalence 2,8% 0,1% Determinants of HPV- and CIN-positivity Subsequently, the obtained test results were evaluated regarding potential subgroups and demographic determinants. Comparing the localization of the puskesmas the percentage of invalid test results was significantly associated with rural (5.5%) and urban (1.2%) primary care units (p < 0.001). However, similar differences were not identified regarding the test results (HPV-positivity 2.4% vs. 2.7%). Overall, there was a trend for higher CIN-positivity rates in rural than in urban areas (25.0% vs. 10.4% of all colposcopies; p = 0.054). High risk CIN2 + was evenly distributed (prevalence 0.1%). Age groups were not associated with the technical test validity (p = 0.982). HPV positivity was also not related to the age of the participants and high-risk genotypes HPV16/18 were detected in all investigated age groups. In contrast, CIN-positivity was significantly different (p < 0.05) between the various age groups and most prominent in the groups 40–44 years (53.3% of all CIN-positive participants; Table 3 ). By comparing the educational level of the participants and their marriage status significant differences regarding test validity (p = 0.582; p = 961) and HPV-positivity (p = 0.720; p = 0.983) were not found. Table 3 Age-dependence of test validity, HPV prevalence and CIN-positivity Age group [years] < 35 35–39 40–44 45–49 ≥ 50 # tested participants 285 401 461 416 165 % invalid test in age group 0,7% 0,3% 0,4% 1,0% 0,6% % of all HPV-positive 18,8% 22,9% 27,1% 14,6% 12,5% % HPV + in age group 3,2% 2,8% 2,8% 1,7% 3,7% % of all CIN+ 13,3% 6,7% 53,3% 6,7% 20,0% Multivariate test approach A binomial logistic regression was performed to determine the effect of age, rural/urban location, marriage status, educational level and HPV genotypes predict the likelihood of CIN-positivity. All 92 participants with sufficient colposcopy were included in this modelling. The model was statistically significant (χ² (12) = 39,390, p < .001), resulting in a large amount of explained variance , as shown by Nagelkerke’s R² = 0.597. Overall, obtained accuracy in classification was 88.9%, with a specificity of 93.3% and a sensitivity of 66.7%. Of the five variables entered into the regression model, age (p = 0.019), HPV type (p = 0.003) and education level (p = 0.006) contributed significantly as predictors for CIN-positivity, whereas rural/urban environment (p = 0.771) and martial status (p = 1.0) did not. HPV negativity in women aged > 40 years excluded CIN positivity in our cohort. All model coefficients and odds can be found in table suppl. 2. Discussion Cervical cancer ranks as the fourth most common cancer among women globally and is the second most common cancer in Indonesia. , Around 70% of Indonesian women are diagnosed at advanced stages, underscoring the need of screening programs in early detection. Despite Indonesia’s national cervical cancer screening program aligned with WHO guidelines, research indicates that merely 12% of women aged 30–49 participate in screening programs. Different strategies have been suggested to improve this participation rate, all of them facing various implementation barriers. Therefore, our investigation focused on the implementation of HPV-based self-sampling within a primary care setting. Among the 1958 women in our study who underwent technically valid HPV-testing, we observed a surprisingly low estimated prevalence of 2.6% in the target population that is below reported results for Indonesia and other LMICs in Asia. 5, 7, 8, 10, This is in line with the low rate of 0.1% for high-risk HPV2 + in the investigated target population. Since the study design can be considered as representative sampling for this region this low prevalence seems to be influenced by other factors. Differences between rural and urban areas were not clearly shown in our study. The HPV immunization program for Indonesia has not been implemented in a manner yet that could modulate HPV or CIN occurrence. Health literacy, educational level, religious/cultural background and sexual behavior 20, , , among others, have been discussed as determinants. These factors have been investigated in our study using the accompanying questionnaire approach and its results will be published separately. Our study examined four different swab- or urine-based devices for HPV-based self-sampling. Significant differences in the technical validity of DNA detection were found among the devices and UriSponge® had to be skipped from further investigation due to insufficient technical test validity. This is likely caused by the smaller amount of collected urine (3 ml) in this device resulting in insufficient cell content in the specimens. The other three devices achieved acceptable detection rates over 90% without significant differences. MSwab® achieved the highest performance with a 99.7% detection rate, while VibaBrush® was less effective at 92.1%, likely due to its softer swab brush. The urine test ColliPee® also performed well, with a detection rate of 99.4%. We found slightly more invalid tests in rural compared to urban areas but not across various age groups, concerning marital status or educational level, suggesting that woman in rural regions may have more difficulties with the self-sampling procedure. Overall, these results support the technical suitability of both swab and urine tests for effective HPV detection based on self-sampling, offering flexible options for screening programs even under primary care conditions where only assistance of midwifes is available. It should be accompanied by a targeted training of self-sample handling in rural settings. Several patients who tested positive for cervical cancer screening did not receive recommended follow-up with biopsy or treatment. Feedback on reasons included fear for results, restrictions by husbands and families, and travel distance from the referral hospital. 22,25 Comparable to other countries some barriers for cervical cancer screening are multifaceted and require a holistic approach addressing simultaneously the health system, individual, cultural, community, and structural levels. 19 Capacity building is needed involving various health and non-health sectors. For example, the social environment of the targeted women, such as cadres, village heads, husbands and families, need to be empowered by socializing the importance of cervical cancer screening and follow-up. Compliance and literacy of cervical cancer screening, especially in rural areas, are influenced by preexisting motherhood. Mothers are better aware of the importance to maintain reproductive health that frequently translates into knowledge regarding early detection of cervical cancer and higher compliance with visiting health care facilities. 5 In addition, husband's support is an important factor in mothers' decision-making in undergoing cervical cancer screening. 9, 13 Therefore, it is necessary to educate husbands and the wider community for support of cervical cancer screening for the targeted women. 9, 13, 19 Midwives, nurses, general practitioners and obstetricians need to accept an active role in educating the involved stakeholders for cancer literacy and cervical cancer management. 5, 7 All women who were tested positive for HPV underwent a colposcopy, along with an equal number of randomly selected HPV-negative women. Among the target population, 16 cases of CIN-positive women were identified with only two cases as high-risk CIN2+ (0.1%). The rates of CIN-positivity significantly differed across age groups, being most prominent in the 40–44 years group that is consistent with other studies. , The performance of the HPV detection for exclusion of women at risk was high and comparable to previously published investigations. , , Detection with a specificity of 97.7% and NPV of 100% for high-risk CIN2 + predisposition support the suitability of a midwife-assisted self-sampling as primary care approach. This high NPV was underlined by the regression analysis that confirmed exclusion of CIN + in HPV-negative women above 40 years of age. However, although it is related to the prevalence the low PPV (4.5%) of HPV-detection for identification of high-risk women is a known shortcoming of this screening approach. 8 It suggests combined screening concepts or multimodal testing to narrow down the number of participants that require intensified diagnostics and potentially treatment. Both our study and others 20, , have identified a high proportion of high-risk HPV genotypes within the HPV-positive groups. In our HPV-positive population, 29.4% were found to carry high-risk genotypes, HPV16 and HPV18, or HPV16 in combination with other genotypes. In addition, other high-risk genotypes (HPV52 and HPV58) were also previously identified among Indonesian women 20, 35 , which were not separately evaluated in our study. Regional differences within the country regarding cultural and behavioral background as potential determinants of HPV-positivity and related high-risk CIN2 + lesions may occur and should be addressed in future evaluations. While the acceptance rate for colposcopy was high, with only 2% refusal rate for further clinical evaluation, the accuracy of the procedure performed by healthcare professionals was suboptimal. In 6.1% of colposcopies, an insufficient amount of material was collected, resulting in invalid cytological/histological results. This is in line with the limited availability of high-quality colposcopy services and histopathologic laboratories in low-resource settings. Despite its undisputable role to cervical cancer prevention in experienced hands, the overall performance of colposcopy is often unsatisfactory in LMICs. Diagnostic accuracy for cervical biopsy in detecting CINs is notably low, ranging from 30–70%, particularly in these environments. This limitation has to be considered when conceptualizing effective screening approaches for Indonesia. Although PAP smear has been described with the best cost effectiveness of screening in this country , pre-test limitations of these procedures that are intensively related to individual knowledge and expertise need to be integrated into national concepts. For example, if HPV-testing is done in a VIA preselected screening population its sensitivity for high-risk CIN2 + drops to 67% referring to a high false negative rate. Although our study has the strength of covering a complete district in Indonesia in a representative manner representing rural and urban areas it also has some shortcomings. Two most remote puskesmas encountered specific challenges with participant recruitment and data collection. In addition, recruitment was done on a subsequent basis within the puskesmas and some selection bias could not be fully avoided. Midwives' recruitment challenges in primary care – although well trained before participation as study site - may have led to a biased selection of participants, focusing on those more easily reachable or compliant. However, the demographic characteristics of the recruited women is highly comparable to the countries demography, but the investigated district is not representative for the entire country, such as the metropolitan region of Jakarta. Comparative evaluation should be done as basis for national screening strategies. Because of limited colposcopy capacities in the given environment, we could not provide colposcopies for all participants. Instead, we examined a randomly selected group of HPV-negative participants equal in size to the HPV-positive group (matched pair approach). To represent the entire study cohort their results were projected towards the entire HPV-negative group resulting in an inherent uncertainty due to the relatively small HPV prevalence. In addition, 6% of invalid biopsies during colposcopy even after training of the involved gynecologists pointed to the above mentioned limitation for a roll-out of this approach as screening for Indonesia. Besides the limitations and challenges discussed, it is essential to highlight the growing acceptance of self-sampling methods for HPV detection as a primary approach for early cervical cancer detection. The self-sampling approach offers many benefits, including increased privacy, convenience, and potentially higher participation rates, especially in rural and hard-to-reach areas. In addition, molecular-based detection is much more independent from individual diagnostic competences, once self-sampling is properly performed. Our findings have shown that self-sampling based HPV-detection can be performed even under primary care conditions in an LMIC region with a sufficient technical test quality. This can be considered as viable and effective method for the early detection of cervical cancer if it is combined with appropriate community engagement and education. However, successful implementation will require addressing technical and logistical challenges, ensuring the accuracy of self-collected samples, and maintaining high standards for diagnostic performance and follow-up care. The very high PPV for HPV detection as most important risk factor for cervical cancer development appear to be useful as primary screening tool. However, the relatively low PPV for identification of high-risk CIN 2 + suggests a combined, multimodal test approach. This should be investigated in future studys. Declarations Authors' contributions The authors contributed in the following manner: SW: Concept, Data Provision, Data Analysis, Data and Result in Interpretation, Writing and Discussion. DS : Data and Result in Interpretation, Writing and Discussion. SS : Data and Result in Interpretation, Writing and Discussion. LF: Data and Result in Interpretation, Writing and Discussion. SS: Data and Result in Interpretation, Writing and Discussion, WK: Data and Result in Interpretation, Writing and Discussion, AW: Data and Result in Interpretation, Writing and Discussion, AD: Data and Result in Interpretation, Writing and Discussion, OE: Concept, Data and Result in Interpretation, Writing and Discussion, MAZ: Data and Result in Interpretation, Writing and Discussion. AK: Data and Result in Interpretation, Writing and Discussion, DSN : Data and Result in Interpretation, Writing and Discussion , MSH: Data and Result in Interpretation, Writing and Discussion, FDT : Data and Result in Interpretation, Writing and Discussion. BAO: Data and Result in Interpretation, Writing and Discussion, PW: Data and Result in Interpretation, Writing and Discussion, PH: Concept, Data Provision, Data Analysis, Data and Result in Interpretation, Writing and Discussion, JH: Concept, Data Provision, Data Analysis, Data and Result in Interpretation, Writing and Discussion. All authors contributed to the article and approved the submitted version. Competing interests All other authors do not have competing interests. Acknowledgements The authors acknowledge the support of the companies Roche®, Novosanis®, Copan® and Rovers® during the study. The authors are very thankful for the intensive political support by the Governor of the Province of Yogyakarta and the province Ministry of Health. In addition, the authors are very thankful for the contribution from all IndoCerCa Team including : dr. Diannisa Ikarumi Enisar Sangun, Sp.OG(K), Dr. dr. Shinta Prawitasari, M.Kes., Sp.OG(K), Sutantri, S.Kep., Ns., MSc., Ph. D, Dianita Sugiyo, S.Kep., Ns., MHID, Dr. dr. Arlina Dewi, M.Kes and Dwi Astuti, SIP. Data sharing Anonymized data are available from the corresponding author on reasonable request. Ethics approval and consent to participate Ethical approval was obtained from the Gadjah Mada University (KE/FK/1445/EC) for the entire project. All methods were performed in accordance with the relevant guidelines and regulations (Declaration of Helsinki). Funding This project was supported by grants from Centre for Research, Publication, and Community Development Muhammadiyah University of Yogyakarta (SW), and funded by the German Ministry of Research and Education under the Global Health Research Alliance (JH; GLOHRA, No: 01KA2104). References WHO. Cervical cancer. Cervical cancer. 2024. https://www.who.int/news-room/fact-sheets/detail/cervical-cancer . Accessed 20 Jun 2024 Nyngsi E, Rauf S, Moeljono E. Sensitivity and Specificity of the Self­-Administered HPV Testing in Detecting Precancerous Conditions of the Cervix and Cervical Cancer. Indonesian Journal of Obstetrics and Gynecology. 2017;5:173–9 Chan CK, Aimagambetova G, Ukybassova T, Kongrtay K, Azizan A. Human Papillomavirus infection and cervical cancer: Epidemiology, screening, and vaccination-review of current perspectives. 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High sensitivity and specificity rates of cobas® HPV test as a primary screening test for cervical intraepithelial lesions in a real-world setting. PLoS One. 2023;18:e0279728 Khakwani M, Parveen R, Azhar M. Comparison of PAP smear and liquid based cytology as a screening method for cervical carcinoma. Pak J Med Sci Q. 2022;38:1827–31 Ekawati FM, Listiani P, Idaiani S, Thobari JA, Hafidz F. Cervical cancer screening program in Indonesia: is it time for HPV-DNA tests? Results of a qualitative study exploring the stakeholders’ perspectives. BMC Womens Health. 2024;24:125 Apgar BS, Zoschnick L, Wright TC Jr. The 2001 Bethesda System terminology. Am Fam Physician. 2003 Nov 15;68(10):1992-8. PMID: 14655809 Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2006). Multivariate Analysemethoden: Eine anwendungsorientierte Einführung (11th ed.). Berlin: Springer. Arbyn, M., Weiderpass, E., Bruni, L., de Sanjosé, S., Saraiya, M., Ferlay, J., & Bray, F. (2020). Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. The Lancet Global Health, 8(2), e191–e203. https://doi.org/10.1016/S2214-109X(19)30482-6 Complementary data on cervical cancer prevention. Retrieved June 26, 2024, from www.hpvcentre.net National Cervical Cancer Elimination Plan for Indonesia 2023–2030. Retrieved October 10th, 2024 from https://kemkes.go.id/id/national-cervical-cancer-elimination-ncce-plan-for-indonesia-2023-2030 Maxi, G., Robbers, L., Bennett, L. R., Rina, B., Spagnoletti, M., & Wilopo, S. A. (2021). Facilitators and barriers for the delivery and uptake of cervical cancer screening in Indonesia: a scoping review. https://doi.org/10.1080/16549716.2021.1979280 Vet, J. N. I., De Boer, M. A., Van Den Akker, B. E. W. M., Siregar, B., Lisnawati, Budiningsih, S., Tyasmorowati, D., Moestikaningsih, Cornain, S., Peters, A. A. W., & Fleuren, G. J. (2008). Prevalence of human papillomavirus in Indonesia: a population-based study in three regions. British Journal of Cancer, 99(1), 214. https://doi.org/10.1038/SJ.BJC.6604417 National Launch of Human Papillomavirus (HPV) Immunization Expansion. Retrieved October 10th, 2024 from https://www.who.int/indonesia/news/detail/09-08-2023-national-launch-of-human-papillomavirus-(hpv)-immunization-expansion . Whitton AF, Knight GL, Marsh EK. Risk factors associated with oral Human Papillomavirus (HPV) prevalence within a young adult population.BMC Public Health. 2024 Jun 3;24(1):1485. doi: 10.1186/s12889-024-18977-x . PMID: 38831431 Berza N, Zodzika J, Kivite-Urtane A, Baltzer N, Curkste A, Pole I, Nygård M, Pärna K, Stankunas M, Tisler A, Uuskula A. Understanding the high-risk human papillomavirus prevalence and associated factors in the European country with a high incidence of cervical cancer. Eur J Public Health. 2024 Aug 1;34(4):826–832. doi: 10.1093/eurpub/ckae075 . PMID: 38822674 Sanad, A. S., Kamel, H. H., & Hasan, M. M. (2014). Prevalence of cervical intraepithelial neoplasia (CIN) in patients attending Minia Maternity University Hospital. Archives of Gynecology and Obstetrics, 289(6), 1211–1217. https://doi.org/10.1007/S00404-013-3109-0/TABLES/3 . Bao, H., Ma, L., Zhao, Y., Song, B., Di, J., Wang, L., Gao, Y., Ren, W., Wang, S., Wu, J., & Wang, H. J. (2022). Age‐specific effectiveness of primary human papillomavirus screening versus cytology in a cervical cancer screening program: a nationwide cross‐sectional study. Cancer Communications, 42(3), 191. https://doi.org/10.1002/CAC2.12256 Kittisiam T, Chanpanitkitchot S, Tangjitgamol S, Srijaipracharoen S, Manusirivithaya S, Srisomboon J, Termrungruanglert W. Clinical Performance of Self-collected Specimen HPV-DNA vs Clinician- collected Specimen HPV-mRNA to Detect High-risk HPV and High-grade Cervical Lesions and Cancer.Asian Pac J Cancer Prev. 2024 Jan 1;25(1):211–217. doi: 10.31557/APJCP.2024.25.1.211 . PMID: 38285786 Bogale AL, Teklehaymanot T, Ali JH, Kassie GM, Medhin G, Baye AY, Shiferaw AY. Comparison of self-collected versus clinician collected cervicovaginal specimens for detection of high risk human papillomavirus among HIV infected women in Ethiopia. BMC Womens Health. 2022 Sep 1;22(1):360. doi: 10.1186/s12905-022-01944-2 . PMID: 36050660 Nutthachote P, Oranratanaphan S, Termrungruanglert W, Triratanachat S, Chaiwongkot A, Baedyananda F, Bhattarakosol P. Comparison of detection rate of high risk HPV infection between self-collected HPV testing and clinician-collected HPV testing in cervical cancer screening. Taiwan J Obstet Gynecol. 2019 Jul;58(4):477–481. doi: 10.1016/j.tjog.2019.05.008 . PMID: 31307736 Human Papillomavirus and Related Diseases Report INDONESIA. Retrieved October 10th, 2024, from https://hpvcentre.net/statistics/reports/IDN.pdf Wulandari, D., Meidyandra, R. W., & Andrijono. (2023). Genotype profiles of high-risk human papillomavirus in women of reproductive age: A community-based study. PLOS ONE, 18(7). https://doi.org/10.1371/JOURNAL.PONE.0287399 Nuranna, L., Aziz, M. F., Cornain, S., Purwoto, G., Purbadi, S., Budiningsih, S., Siregar, B., & Peters, A. A. W. (2012). Cervical cancer prevention program in Jakarta, Indonesia: See and Treat model in developing country. Journal of Gynecologic Oncology, 23(3), 147. https://doi.org/10.3802/JGO.2012.23.3.147 Xue, P., Ng, M. T. A., & Qiao, Y. (2020). The challenges of colposcopy for cervical cancer screening in LMICs and solutions by artificial intelligence. BMC Medicine, 18(1). https://doi.org/10.1186/S12916-020-01613-X Nam, K. (2018). Colposcopy at a turning point. Obstetrics & Gynecology Science, 61(1), 1–6. https://doi.org/10.5468/OGS.2018.61.1.1 Hafidz F, Icanervilia AV, Rizal MF, Listiani P, Setyaningsih H, Sasanti ML, Ekawati FM, Atthobari JA, Utami TW, Trirahmanto A, Tjokroprawiro BA, Harsono AB, Masytoh LS, Haryani W, Subekti Y, Nadjib M. Economic Evaluation of Cervical Cancer Screening by HPV DNA, VIA, and Pap smear Methods in Indonesia.Asian Pac J Cancer Prev. 2024 Sep 1;25(9):3015–3022. doi: 10.31557/APJCP.2024.25.9.3015 . PMID: 39342578 John JH, Halder A, Purwar S, Pushpalatha K, Gupta P, Dubey P. Study to determine efficacy of urinary HPV 16 & HPV 18 detection in predicting premalignant and malignant lesions of uterine cervix.Int J Gynaecol Obstet. 2023 Apr;161(1):79–85. doi: 10.1002/ijgo.14486 . Epub 2022 Oct 14. PMID: 36184575 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7429458","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510095695,"identity":"0db28e7f-c2cd-4b79-959b-4005fe4c52d0","order_by":0,"name":"Supriyatiningsih 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School","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Hillemanns","suffix":""},{"id":510095721,"identity":"059e9466-0aaf-4317-a54f-be0dab24671a","order_by":14,"name":"Jörg Haier","email":"","orcid":"","institution":"Universitas Muhammadiyah Yogyakarta","correspondingAuthor":false,"prefix":"","firstName":"Jörg","middleName":"","lastName":"Haier","suffix":""}],"badges":[],"createdAt":"2025-08-21 22:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7429458/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7429458/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91074533,"identity":"b79ccc3f-5870-45f1-870c-ed1466e66f5c","added_by":"auto","created_at":"2025-09-11 11:03:17","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":107047,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA diagram for study cohort\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7429458/v1/9d3ce03b13bbed294965f38f.jpeg"},{"id":91074532,"identity":"9b93285d-14ae-4b3a-9a0f-573a3dead1a0","added_by":"auto","created_at":"2025-09-11 11:03:17","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":82430,"visible":true,"origin":"","legend":"\u003cp\u003ea) Technical validity rate for sampling devices; b) HPV-DNA detection rates for different self-sampling devices; c) Occurrence of HPV genotypes in HPV-positive women; d) CIN results in HPV-positive participants\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7429458/v1/03b590fd935a2eeb417ca05a.jpeg"},{"id":91080335,"identity":"592dbf94-0e5f-4e31-b1e9-ce45bdb5fb54","added_by":"auto","created_at":"2025-09-11 11:35:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":958207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7429458/v1/f40a335a-0953-430f-8984-76a6d5fd872d.pdf"},{"id":91076597,"identity":"cbf03a9f-c377-4878-bec0-1cbaa31e5021","added_by":"auto","created_at":"2025-09-11 11:11:18","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":30777,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfileindocerca.docx","url":"https://assets-eu.researchsquare.com/files/rs-7429458/v1/b0b90c721673362e15727a5d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Population-based self-sampling under primary care conditions – a possible approach for cervical cancer screening in Indonesia (IndoCerCa study)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe public health challenge of cervical cancer continues to be significant, especially in low- and middle-income countries (LMICs). Globally, it is the fourth most common cancer among women, with approximately 660,000 new cases and 350,000 deaths reported in 2022.\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e The early detection of cervical cancer in Indonesia is crucial due to its leading cause among cancer-related deaths in women, highlighting the critical importance of implementing effective screening methods.\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003c/a\u003e\u003c/p\u003e\u003cp\u003eHuman Papillomavirus (HPV) infection is the primary cause of cervical cancer, with high-risk HPV (HR-HPV) types leading to cervical intraepithelial neoplasia (CIN) and invasive cervical cancer.\u003ca class=\"FNLink\" href=\"#Fn3\" id=\"#FNLinkFn3\"\u003e\u003c/a\u003e Effective screening relies on two critical metrics: sensitivity (the ability to identify those with the disease correctly) and specificity (the ability to properly identify those without the disease).\u003ca class=\"FNLink\" href=\"#Fn4\" id=\"#FNLinkFn4\"\u003e\u003c/a\u003e The current population-based approach in Indonesia using visual inspection (VIA) suffers severely from related shortcomings and low rates of predictive accuracy.\u003c/p\u003e\u003cp\u003eUnderstanding HR-HPV prevalence across Asia is crucial for targeted prevention and treatment strategies. For example, in Malaysia HR-HPV prevalence is 4.53% with HPV16/18 at 1.23% and other high-risk types at 3.30%.\u003ca class=\"FNLink\" href=\"#Fn5\" id=\"#FNLinkFn5\"\u003e\u003c/a\u003e In contrast, for China HR-HPV prevalence has been reported as 9.9% with HPV16/18 at 2.4% and other high-risk types at 7.5%\u003ca class=\"FNLink\" href=\"#Fn6\" id=\"#FNLinkFn6\"\u003e\u003c/a\u003e and among women aged 30\u0026ndash;64 as 14.4% and 4.7%, respectively.\u003ca class=\"FNLink\" href=\"#Fn7\" id=\"#FNLinkFn7\"\u003e\u003c/a\u003e In Hong Kong, HR-HPV prevalence is 8.75%, with HPV16 in 1.15% and HPV18 in 0.61% of women.\u003ca class=\"FNLink\" href=\"#Fn8\" id=\"#FNLinkFn8\"\u003e\u003c/a\u003e In Korea, HR-HPV prevalence ranges from 8.02\u0026ndash;11.45%, with HPV52 notably high at 17.26%.\u003ca class=\"FNLink\" href=\"#Fn9\" id=\"#FNLinkFn9\"\u003e\u003c/a\u003e In Thailand, HR-HPV prevalence is 5.6%, with HPV16/18 at 1.7%.\u003ca class=\"FNLink\" href=\"#Fn10\" id=\"#FNLinkFn10\"\u003e\u003c/a\u003e Another Thai study reported prevalence of abnormal cervical cytology rates of 4.8% with conventional Pap smears and 5.7% with liquid-based Pap smears (LBP).\u003ca class=\"FNLink\" href=\"#Fn11\" id=\"#FNLinkFn11\"\u003e\u003c/a\u003e\u003c/p\u003e\u003cp\u003eWithin the Asian environment, primary HPV testing appears to be more effective than cytology-based methods for detecting CIN2\u0026thinsp;+\u0026thinsp;lesions. In China, primary HPV testing showed a significantly higher sensitivity for detecting CIN2\u0026thinsp;+\u0026thinsp;than cytology.\u003csup\u003e7\u003c/sup\u003e Similarly, in Hong Kong, Korea and other Asian investigations, HPV-DNA detection exhibited high sensitivity and specificity.\u003csup\u003e8, 9, 11,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn12\" id=\"#FNLinkFn12\"\u003e\u003c/a\u003e HPV primary screening with more advanced cytology diagnostics, such as p16/Ki-67 dual stain, showed higher sensitivity for CIN2\u0026thinsp;+\u0026thinsp;detection than conventional Pap smears.\u003csup\u003e10,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn13\" id=\"#FNLinkFn13\"\u003e\u003c/a\u003e However, all these high performance screening approaches suffer from implementation barriers, especially in LMICs mainly due to economic restrictions, insufficient availability of qualified personnel or lack of acceptance within the target population.\u003c/p\u003e\u003cp\u003eEffective screening can significantly reduce cervical cancer mortality rates. HPV self-sampling allows women to collect samples at home and can increase screening coverage and early diagnosis. Self-sampling is available using swab- or urine based collection. These obtained specimens need to be processed properly to obtain valid results. Automated systems for HPV-DNA detection can subsequently reduce technical failure and insufficient detection rates. However, challenges, such as limited national insurance reimbursements, government regulations, lack of clinician awareness, and limited availability of HPV-DNA testing in Indonesia must be addressed for a potential roll-out.\u003ca class=\"FNLink\" href=\"#Fn14\" id=\"#FNLinkFn14\"\u003e\u003c/a\u003e Cultural barriers, including fear, shyness, and anxiety about screening procedures and results, also impact participation\u003csup\u003e14\u003c/sup\u003e and need to be evaluated. For a national roll-out, especially in a country with relevant access barriers, such as due to remote and rural population, these screening approaches need to work under primary care conditions.\u003c/p\u003e\u003cp\u003eTherefore, we investigated the usability of different self-sampling devices for HPV-DNA detection under primary care condition covering an entire district in Indonesia. This was combined with the development of a training program for the involved midwifes as blue-print for subsequent potential roll-out. Technical and clinical test performance were combined with an evaluation of acceptance barriers.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eStudy design\u003c/h3\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eTarget population\u003c/h2\u003e\u003cp\u003ePrimary care setting was applied by conducting self-sampling in primary care units (Puskesmas) in the district of Kulon Progo, Yogyakarta Province, Indonesia. All of these puskesmas were randomly assigned to one of the self-sampling devices with stratification according to rural/urban and urine/swab distribution. (Suppl. Table\u0026nbsp;1) According to the legal Indonesian framework all puskesmas can be attributed regarding the covered region and population. This provided a distinction between rural (n\u0026thinsp;=\u0026thinsp;13) and urban (n\u0026thinsp;=\u0026thinsp;8) recruitment areas enabling a cluster randomization for the usage of the self-sampling devices (urine n\u0026thinsp;=\u0026thinsp;10, swab n\u0026thinsp;=\u0026thinsp;11).\u003c/p\u003e\u003cp\u003eInvitations for study participation were send to randomly selected women within each puskesmas coverage population in the respective age by the local Ministry of Health (MoH). This ensured participation also for women in remote areas. Traveling costs related to study participation were reimbursed. Women were eligible in an age of 30\u0026ndash;55 years, non-pregnant without history of cancer. 100 participants per involved puskesmas were targeted, thus an overall recruitment of 2.100 women.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAcceptance evaluation\u003c/h3\u003e\n\u003cp\u003eIn addition to the self-sampling, the participants were asked to fill-out a validated acceptance questionnaire. This questionnaire contained 26 questions with overall 130 subitems covering the domains health/cancer literacy, cancer prevention knowledge, coping strategies, acceptance of cervical cancer screening. In addition, demographic data (age, education, social environment) were obtained. If applicable, equidistant rating scales were applied and the validation was done involving local midwifes and volunteer laypersons.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003ewas given by the Gadjah Mada University (KE/FK/1445/EC). Informed consent was obtained by all participants before recruitment into the study. Registration was not required due to the non-interventional and observational character of the investigation.\u003c/p\u003e\u003c/p\u003e\n\u003ch3\u003eDiagnostic algorithm\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eSelf-sampling\u003c/h2\u003e\u003cp\u003ePrior to recruitment all involved midwifes in the participating puskesmas were trained regarding the handling of the self-sampling devices and informed consent procedures. Written and video-clip explanatory material about the device handling was provided for the recruited women before self-sampling. Midwifes were allowed to support the women in handling and all samples were obtained within the primary care units (home-based self-sampling was excluded). The following devices were used in the study group I: UriSponge\u0026trade; (Copan\u0026reg;); group II: Viba Brush\u0026reg; (Rovers\u0026reg;); group III: Colli-Pee 10 mL UCM (Novosanis\u0026reg;); group IV: MSwab\u0026reg; 6E067N (Copan\u0026reg;). Storage and transportation of the samples to the central laboratory for testing was performed according to the manufactures\u0026rsquo; instructions.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHPV-detection\u003c/h3\u003e\n\u003cp\u003eDetection of HPV \u0026ndash;DNA was done using the standard procedures of the Cobas\u0026reg; 4800 HPV system (Roche\u0026reg;). HPV-16, HPV-18 and other HPV-genotypes were differentiated. Prior to testing the lab staff was specifically trained and a technical pilot test phase was performed. This pilot investigation evaluated the entire pre-diagnostic chain and provided a technical validation based on 75 participants for each sampling device.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eClinical validation\u003c/h2\u003e\u003cp\u003eAll participating women were informed about their HPV-test results by the primary care structures. HPV-positive women were invited to colposcopy and further clinical evaluation. For evaluation of test results a randomly selected group of HPV-negative participants (similar number as for HPV-positive) was included in the clinical validation group. Full coverage of clinical validation for all participants could not been done due to resource limitations for colposcopy under the targeted real-life conditions. This clinical examination was conducted in a specialized center at Sardjito Hospital, a vertical hospital in Yogyakarta province within an advanced care hospital. It included colposcopy, PAP smear and a cervical biopsy. Reporting of the cytology and histology results was done according to international guidelines.\u003ca class=\"FNLink\" href=\"#Fn15\" id=\"#FNLinkFn15\"\u003e\u003c/a\u003e CIN-positive women were subsequently treated based on the Indonesian national algorithms that are ruled by the respective MoH.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003eTest evaluation\u003c/h2\u003e\u003cp\u003ePrevalence of HPV-positivity and precancerous lesions was determined. Sensitivity, specificity and predictive values were calculated for the self-sampling approaches based on the clinical validation results and back-calculation of HPV-negative evaluation.\u003c/p\u003e\u003cp\u003eCross table comparison was done using Chi\u0026sup2;-tests and, when appropriate, Pearson contingency coefficient and Cramer\u0026rsquo;s V were used.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMultivariate analysis\u003c/h2\u003e\u003cp\u003eFor multivariate analysis potential interactions between various variables werre addressed. Collinearity was assumed for variables with R\u0026thinsp;\u0026gt;\u0026thinsp;0.8 in cross-correlations. ANOVA method was applied for univariate group comparison. Scheff\u0026eacute; procedure and Bonferoni correction were done for multivariate analyses and related post-hoc tests.\u003c/p\u003e\u003cp\u003eFor logistic regression modelling all related variables in each test approach were evaluated using CIN-positivity or high risk CIN2\u0026thinsp;+\u0026thinsp;as dependent target parameter. Age groups, rural/urban location, marriage status, educational level and HPV genotypes were tested as potential independent determinants. The obtained regression functions were evaluated based on the 2-fold log likelihood and Chi\u0026sup2;-tests. Nagelkerke-R\u0026sup2; was used to explain the variance of the regression model with values\u0026thinsp;\u0026gt;\u0026thinsp;0.5 suggesting relevant determinants.\u003c/p\u003e\u003cp\u003eAll statistical analyses were performed using IBM SPSS Statistics Version 29.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eTechnical validation of self-sampling devices\u003c/h2\u003e\u003cp\u003eIn a first pilot group (n\u0026thinsp;=\u0026thinsp;295) the technical performance of each self-sampling device was evaluated. In this group Colli-Pee and MSwab\u0026reg; showed 100% detection rates for human DNA, whereas Viba Brush\u0026reg; had valid testing in 76.5% and UriSponge\u0026trade; in only 5.6% of the analyzed 36 participants. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) Therefore, the latter device was excluded from the subsequent evaluation and replaced by self-sampling using the second urine-based device (Colli-Pee). A second urine-based self-sampling was offered to all participants in this group.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003ePerformance of study cohort\u003c/h2\u003e\u003cp\u003eOverall, 2056 participants were recruited and 2020 women were included in the final evaluation. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Using the three sampling devices, for 1958 participants technically valid HPV testing was obtained with final DNA detection rates of 92.1% for Viba Brush\u0026reg;, 99.4% for Colli-Pee and 99.7% for MSwab\u0026reg; (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). This association of the technical validity with the sampling devices was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Age was not significantly different between urban (41.17\u0026thinsp;\u0026plusmn;\u0026thinsp;6.52 years) and rural (40.80\u0026thinsp;\u0026plusmn;\u0026thinsp;6.29 years) participants (p\u0026thinsp;=\u0026thinsp;0.28).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eDetection of HPV-DNA\u003c/h2\u003e\u003cp\u003eHPV-DNA was detected in 51 cases reflecting 2.6% prevalence in the target population. This detection rate differed slightly, but not significantly between the sampling devices (2.3% \u0026minus;\u0026thinsp;2.9%) or the sampling method (urine: 2.4%; swab 2.8%). (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) In 29.4% of the HPV-positive women high risk genotypes (HPV16/18) were detected. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) In two cases HPV16 infection was combined with other HPV genotypes. This genotype distribution was comparable for the devices or the sampling methods and also not significantly associated with applied technology.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTest results for HPV-DNA detection by self-sampling devices\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eurine\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eswab\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003etotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDevice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUriSponge\u0026trade;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColli-Pee UCM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eViba Brush\u0026reg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMSwab\u0026reg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e# participants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.06\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.06\u0026thinsp;\u0026plusmn;\u0026thinsp;6.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.18\u0026thinsp;\u0026plusmn;\u0026thinsp;6.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40.82\u0026thinsp;\u0026plusmn;\u0026thinsp;6.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e40.94\u0026thinsp;\u0026plusmn;\u0026thinsp;6.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV other\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV multiple*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInvalid**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSum HPV positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSum HPV negative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e918\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e918\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1907\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e# HPV valid tests\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e941\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e941\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e420\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1958\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eValidity rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5,6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99,4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92,1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99,7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV positive rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2,9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2,7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2,8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2,6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e* in both cases HPV16 \u0026amp; HPV others\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e** sufficient detection of human cytokeratin-DNA as positive control was not achieved\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e*** The group of UriSponge\u0026trade; was excluded in the final analysis\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eClinical validation\u003c/h2\u003e\u003cp\u003eOverall, for 100 women colposcopy combined with pap-smear cytology and cervical biopsy (histology) was suggested (51 HPV-positive, 49 HPV-negative). Two of the HPV-positive participants refused further clinical evaluation (refusal rate 2.0%). In 6/98 (5 HPV-positive, 1 HPV-negative) cases the pathological evaluation reported insufficient amounts of material that was classified as invalid colposcopy (6.1%). CIN-positive situations were confirmed in 16 of the evaluable participants (15/44 HPV-positive [34.1%], 1/48 HPV-negative [2.1%]) and two HPV-positive women showed high risk CIN2\u0026thinsp;+\u0026thinsp;results [2/44; 4.5%; none HPV-negative]. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed)\u003c/p\u003e\u003cp\u003eFor calculation of test performance, the randomly selected HPV-negative colposcopy group (including drop-out and invalid colposcopy rates) was projected towards the entire HPV-negative participants. These numbers were used to obtain sensitivity, specificity and predictive values (PPV, NPV) for self-sampling HPV-based screening. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e contains these data for identification of CIN-positivity and for detection of the high-risk CIN2\u0026thinsp;+\u0026thinsp;group. Overall, CIN-positivity can be assumed with a prevalence of 2.8% in the target population whereas only 0.1% are expected to have a high-risk CIN2\u0026thinsp;+\u0026thinsp;cervical status. Due to this low prevalence a respective correction for pretest probability was not required.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll CIN positive\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCIN II+\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSensitivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecificity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98,5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive predictive value (PPV)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34,1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative predictive value (NPV)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97,9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100,0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN-prevalence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eDeterminants of HPV- and CIN-positivity\u003c/h2\u003e\u003cp\u003eSubsequently, the obtained test results were evaluated regarding potential subgroups and demographic determinants. Comparing the localization of the puskesmas the percentage of invalid test results was significantly associated with rural (5.5%) and urban (1.2%) primary care units (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, similar differences were not identified regarding the test results (HPV-positivity 2.4% vs. 2.7%). Overall, there was a trend for higher CIN-positivity rates in rural than in urban areas (25.0% vs. 10.4% of all colposcopies; p\u0026thinsp;=\u0026thinsp;0.054). High risk CIN2\u0026thinsp;+\u0026thinsp;was evenly distributed (prevalence 0.1%).\u003c/p\u003e\u003cp\u003eAge groups were not associated with the technical test validity (p\u0026thinsp;=\u0026thinsp;0.982). HPV positivity was also not related to the age of the participants and high-risk genotypes HPV16/18 were detected in all investigated age groups. In contrast, CIN-positivity was significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the various age groups and most prominent in the groups 40\u0026ndash;44 years (53.3% of all CIN-positive participants; Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). By comparing the educational level of the participants and their marriage status significant differences regarding test validity (p\u0026thinsp;=\u0026thinsp;0.582; p\u0026thinsp;=\u0026thinsp;961) and HPV-positivity (p\u0026thinsp;=\u0026thinsp;0.720; p\u0026thinsp;=\u0026thinsp;0.983) were not found.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAge-dependence of test validity, HPV prevalence and CIN-positivity\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e\u003cp\u003eAge group [years]\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e# tested participants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e401\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% invalid test in age group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% of all HPV-positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18,8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22,9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14,6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12,5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% HPV\u0026thinsp;+\u0026thinsp;in age group\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2,8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3,7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% of all CIN+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13,3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53,3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6,7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20,0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eMultivariate test approach\u003c/h2\u003e\u003cp\u003eA binomial logistic regression was performed to determine the effect of age, rural/urban location, marriage status, educational level and HPV genotypes predict the likelihood of CIN-positivity. All 92 participants with sufficient colposcopy were included in this modelling. The model was statistically significant (χ\u0026sup2; (12)\u0026thinsp;=\u0026thinsp;39,390, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), resulting in a large amount of explained variance\u003ca class=\"FNLink\" href=\"#Fn16\" id=\"#FNLinkFn16\"\u003e\u003c/a\u003e, as shown by Nagelkerke\u0026rsquo;s R\u0026sup2; = 0.597. Overall, obtained accuracy in classification was 88.9%, with a specificity of 93.3% and a sensitivity of 66.7%. Of the five variables entered into the regression model, age (p\u0026thinsp;=\u0026thinsp;0.019), HPV type (p\u0026thinsp;=\u0026thinsp;0.003) and education level (p\u0026thinsp;=\u0026thinsp;0.006) contributed significantly as predictors for CIN-positivity, whereas rural/urban environment (p\u0026thinsp;=\u0026thinsp;0.771) and martial status (p\u0026thinsp;=\u0026thinsp;1.0) did not. HPV negativity in women aged\u0026thinsp;\u0026gt;\u0026thinsp;40 years excluded CIN positivity in our cohort. All model coefficients and odds can be found in table suppl. 2.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCervical cancer ranks as the fourth most common cancer among women globally and is the second most common cancer in Indonesia.\u003ca class=\"FNLink\" href=\"#Fn17\" id=\"#FNLinkFn17\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn18\" id=\"#FNLinkFn18\"\u003e\u003c/a\u003e Around 70% of Indonesian women are diagnosed at advanced stages, underscoring the need of screening programs in early detection.\u003ca class=\"FNLink\" href=\"#Fn19\" id=\"#FNLinkFn19\"\u003e\u003c/a\u003e Despite Indonesia\u0026rsquo;s national cervical cancer screening program aligned with WHO guidelines, research indicates that merely 12% of women aged 30\u0026ndash;49 participate in screening programs.\u003ca class=\"FNLink\" href=\"#Fn20\" id=\"#FNLinkFn20\"\u003e\u003c/a\u003e Different strategies have been suggested to improve this participation rate, all of them facing various implementation barriers.\u003c/p\u003e\u003cp\u003eTherefore, our investigation focused on the implementation of HPV-based self-sampling within a primary care setting. Among the 1958 women in our study who underwent technically valid HPV-testing, we observed a surprisingly low estimated prevalence of 2.6% in the target population that is below reported results for Indonesia and other LMICs in Asia.\u003csup\u003e5, 7, 8, 10,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn21\" id=\"#FNLinkFn21\"\u003e\u003c/a\u003e This is in line with the low rate of 0.1% for high-risk HPV2\u0026thinsp;+\u0026thinsp;in the investigated target population. Since the study design can be considered as representative sampling for this region this low prevalence seems to be influenced by other factors. Differences between rural and urban areas were not clearly shown in our study. The HPV immunization program for Indonesia has not been implemented in a manner yet\u003ca class=\"FNLink\" href=\"#Fn22\" id=\"#FNLinkFn22\"\u003e\u003c/a\u003e that could modulate HPV or CIN occurrence. Health literacy, educational level, religious/cultural background and sexual behavior\u003csup\u003e20,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn23\" id=\"#FNLinkFn23\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn24\" id=\"#FNLinkFn24\"\u003e\u003c/a\u003e, among others, have been discussed as determinants. These factors have been investigated in our study using the accompanying questionnaire approach and its results will be published separately.\u003c/p\u003e\u003cp\u003eOur study examined four different swab- or urine-based devices for HPV-based self-sampling. Significant differences in the technical validity of DNA detection were found among the devices and UriSponge\u0026reg; had to be skipped from further investigation due to insufficient technical test validity. This is likely caused by the smaller amount of collected urine (3 ml) in this device resulting in insufficient cell content in the specimens. The other three devices achieved acceptable detection rates over 90% without significant differences. MSwab\u0026reg; achieved the highest performance with a 99.7% detection rate, while VibaBrush\u0026reg; was less effective at 92.1%, likely due to its softer swab brush. The urine test ColliPee\u0026reg; also performed well, with a detection rate of 99.4%. We found slightly more invalid tests in rural compared to urban areas but not across various age groups, concerning marital status or educational level, suggesting that woman in rural regions may have more difficulties with the self-sampling procedure. Overall, these results support the technical suitability of both swab and urine tests for effective HPV detection based on self-sampling, offering flexible options for screening programs even under primary care conditions where only assistance of midwifes is available. It should be accompanied by a targeted training of self-sample handling in rural settings.\u003c/p\u003e\u003cp\u003eSeveral patients who tested positive for cervical cancer screening did not receive recommended follow-up with biopsy or treatment. Feedback on reasons included fear for results, restrictions by husbands and families, and travel distance from the referral hospital.\u003csup\u003e22,25\u003c/sup\u003e Comparable to other countries some barriers for cervical cancer screening are multifaceted and require a holistic approach addressing simultaneously the health system, individual, cultural, community, and structural levels.\u003csup\u003e19\u003c/sup\u003e Capacity building is needed involving various health and non-health sectors. For example, the social environment of the targeted women, such as cadres, village heads, husbands and families, need to be empowered by socializing the importance of cervical cancer screening and follow-up. Compliance and literacy of cervical cancer screening, especially in rural areas, are influenced by preexisting motherhood. Mothers are better aware of the importance to maintain reproductive health that frequently translates into knowledge regarding early detection of cervical cancer and higher compliance with visiting health care facilities.\u003csup\u003e5\u003c/sup\u003e In addition, husband's support is an important factor in mothers' decision-making in undergoing cervical cancer screening.\u003csup\u003e9, 13\u003c/sup\u003e Therefore, it is necessary to educate husbands and the wider community for support of cervical cancer screening for the targeted women. \u003csup\u003e9, 13, 19\u003c/sup\u003e Midwives, nurses, general practitioners and obstetricians need to accept an active role in educating the involved stakeholders for cancer literacy and cervical cancer management. \u003csup\u003e5, 7\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAll women who were tested positive for HPV underwent a colposcopy, along with an equal number of randomly selected HPV-negative women. Among the target population, 16 cases of CIN-positive women were identified with only two cases as high-risk CIN2+ (0.1%). The rates of CIN-positivity significantly differed across age groups, being most prominent in the 40\u0026ndash;44 years group that is consistent with other studies.\u003ca class=\"FNLink\" href=\"#Fn25\" id=\"#FNLinkFn25\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn26\" id=\"#FNLinkFn26\"\u003e\u003c/a\u003e\u003c/p\u003e\u003cp\u003eThe performance of the HPV detection for exclusion of women at risk was high and comparable to previously published investigations.\u003ca class=\"FNLink\" href=\"#Fn27\" id=\"#FNLinkFn27\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn28\" id=\"#FNLinkFn28\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn29\" id=\"#FNLinkFn29\"\u003e\u003c/a\u003e Detection with a specificity of 97.7% and NPV of 100% for high-risk CIN2\u0026thinsp;+\u0026thinsp;predisposition support the suitability of a midwife-assisted self-sampling as primary care approach. This high NPV was underlined by the regression analysis that confirmed exclusion of CIN\u0026thinsp;+\u0026thinsp;in HPV-negative women above 40 years of age. However, although it is related to the prevalence the low PPV (4.5%) of HPV-detection for identification of high-risk women is a known shortcoming of this screening approach.\u003csup\u003e8\u003c/sup\u003e It suggests combined screening concepts or multimodal testing to narrow down the number of participants that require intensified diagnostics and potentially treatment.\u003c/p\u003e\u003cp\u003eBoth our study and others\u003csup\u003e20,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn30\" id=\"#FNLinkFn30\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e \u003ca class=\"FNLink\" href=\"#Fn31\" id=\"#FNLinkFn31\"\u003e\u003c/a\u003e have identified a high proportion of high-risk HPV genotypes within the HPV-positive groups. In our HPV-positive population, 29.4% were found to carry high-risk genotypes, HPV16 and HPV18, or HPV16 in combination with other genotypes. In addition, other high-risk genotypes (HPV52 and HPV58) were also previously identified among Indonesian women\u003csup\u003e20, 35\u003c/sup\u003e, which were not separately evaluated in our study. Regional differences within the country regarding cultural and behavioral background as potential determinants of HPV-positivity and related high-risk CIN2\u0026thinsp;+\u0026thinsp;lesions may occur and should be addressed in future evaluations.\u003c/p\u003e\u003cp\u003eWhile the acceptance rate for colposcopy was high, with only 2% refusal rate for further clinical evaluation, the accuracy of the procedure performed by healthcare professionals was suboptimal. In 6.1% of colposcopies, an insufficient amount of material was collected, resulting in invalid cytological/histological results. This is in line with the limited availability of high-quality colposcopy services and histopathologic laboratories in low-resource settings.\u003ca class=\"FNLink\" href=\"#Fn32\" id=\"#FNLinkFn32\"\u003e\u003c/a\u003e Despite its undisputable role to cervical cancer prevention in experienced hands, the overall performance of colposcopy is often unsatisfactory in LMICs.\u003ca class=\"FNLink\" href=\"#Fn33\" id=\"#FNLinkFn33\"\u003e\u003c/a\u003e Diagnostic accuracy for cervical biopsy in detecting CINs is notably low, ranging from 30\u0026ndash;70%, particularly in these environments.\u003ca class=\"FNLink\" href=\"#Fn34\" id=\"#FNLinkFn34\"\u003e\u003c/a\u003e This limitation has to be considered when conceptualizing effective screening approaches for Indonesia. Although PAP smear has been described with the best cost effectiveness of screening in this country\u003ca class=\"FNLink\" href=\"#Fn35\" id=\"#FNLinkFn35\"\u003e\u003c/a\u003e, pre-test limitations of these procedures that are intensively related to individual knowledge and expertise need to be integrated into national concepts. For example, if HPV-testing is done in a VIA preselected screening population\u003ca class=\"FNLink\" href=\"#Fn36\" id=\"#FNLinkFn36\"\u003e\u003c/a\u003e its sensitivity for high-risk CIN2\u0026thinsp;+\u0026thinsp;drops to 67% referring to a high false negative rate.\u003c/p\u003e\u003cp\u003eAlthough our study has the strength of covering a complete district in Indonesia in a representative manner representing rural and urban areas it also has some shortcomings. Two most remote puskesmas encountered specific challenges with participant recruitment and data collection. In addition, recruitment was done on a subsequent basis within the puskesmas and some selection bias could not be fully avoided. Midwives' recruitment challenges in primary care \u0026ndash; although well trained before participation as study site - may have led to a biased selection of participants, focusing on those more easily reachable or compliant. However, the demographic characteristics of the recruited women is highly comparable to the countries demography, but the investigated district is not representative for the entire country, such as the metropolitan region of Jakarta. Comparative evaluation should be done as basis for national screening strategies.\u003c/p\u003e\u003cp\u003eBecause of limited colposcopy capacities in the given environment, we could not provide colposcopies for all participants. Instead, we examined a randomly selected group of HPV-negative participants equal in size to the HPV-positive group (matched pair approach). To represent the entire study cohort their results were projected towards the entire HPV-negative group resulting in an inherent uncertainty due to the relatively small HPV prevalence. In addition, 6% of invalid biopsies during colposcopy even after training of the involved gynecologists pointed to the above mentioned limitation for a roll-out of this approach as screening for Indonesia.\u003c/p\u003e\u003cp\u003eBesides the limitations and challenges discussed, it is essential to highlight the growing acceptance of self-sampling methods for HPV detection as a primary approach for early cervical cancer detection. The self-sampling approach offers many benefits, including increased privacy, convenience, and potentially higher participation rates, especially in rural and hard-to-reach areas. In addition, molecular-based detection is much more independent from individual diagnostic competences, once self-sampling is properly performed. Our findings have shown that self-sampling based HPV-detection can be performed even under primary care conditions in an LMIC region with a sufficient technical test quality. This can be considered as viable and effective method for the early detection of cervical cancer if it is combined with appropriate community engagement and education. However, successful implementation will require addressing technical and logistical challenges, ensuring the accuracy of self-collected samples, and maintaining high standards for diagnostic performance and follow-up care. The very high PPV for HPV detection as most important risk factor for cervical cancer development appear to be useful as primary screening tool. However, the relatively low PPV for identification of high-risk CIN 2\u0026thinsp;+\u0026thinsp;suggests a combined, multimodal test approach. This should be investigated in future studys.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eThe authors contributed in the following manner:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSW: Concept, Data Provision, Data Analysis, Data and Result in Interpretation, Writing and Discussion. DS : Data and Result in Interpretation, Writing and Discussion. SS : Data and Result in Interpretation, Writing and Discussion. LF: Data and Result in Interpretation, Writing and Discussion. SS: Data and Result in Interpretation, Writing and Discussion, WK: Data and Result in Interpretation, Writing and Discussion, AW: Data and Result in Interpretation, Writing and Discussion, AD: Data and Result in Interpretation, Writing and Discussion, OE: Concept, Data and Result in Interpretation, Writing and Discussion, MAZ: Data and Result in Interpretation, Writing and Discussion. AK: Data and Result in Interpretation, Writing and Discussion, DSN : Data and Result in Interpretation, Writing and Discussion , MSH: Data and Result in Interpretation, Writing and Discussion, FDT : Data and Result in Interpretation, Writing and Discussion. BAO: Data and Result in Interpretation, Writing and Discussion, PW: Data and Result in Interpretation, Writing and Discussion, PH: Concept, Data Provision, Data Analysis, Data and Result in Interpretation, Writing and Discussion, JH: Concept, Data Provision, Data Analysis, Data and Result in Interpretation, Writing and Discussion. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eAll other authors do not have competing interests.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the support of the companies Roche\u0026reg;, Novosanis\u0026reg;, Copan\u0026reg; and Rovers\u0026reg; during the study. The authors are very thankful for the intensive political support by the Governor of the Province of Yogyakarta and the province Ministry of Health. In addition, the authors are very thankful for the contribution from all IndoCerCa Team including : dr. Diannisa Ikarumi Enisar Sangun, Sp.OG(K), Dr. dr. Shinta Prawitasari, M.Kes., Sp.OG(K), Sutantri, S.Kep., Ns., MSc., Ph. D, Dianita Sugiyo, S.Kep., Ns., MHID,\u003cem\u003e\u0026nbsp;\u003c/em\u003eDr. dr. Arlina Dewi, M.Kes and \u0026nbsp;Dwi Astuti, SIP.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData sharing\u003c/p\u003e\n\u003cp\u003eAnonymized data are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Gadjah Mada University (KE/FK/1445/EC) for the entire project. All methods were performed in accordance with the relevant guidelines and regulations (Declaration of Helsinki).\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis project was supported by grants from Centre for Research, Publication, and Community Development Muhammadiyah University of Yogyakarta (SW), and funded by the German Ministry of Research and Education under the Global Health Research Alliance (JH; GLOHRA, No: 01KA2104).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e WHO. Cervical cancer. 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Epub 2022 Oct 14. PMID: 36184575\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Screening, human papilloma virus, cervical cancer, self-sampling, prevalence","lastPublishedDoi":"10.21203/rs.3.rs-7429458/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7429458/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: In LMIC cervical cancer is a major burden. Screening is mainly based on visual inspection lacking sufficient sensitivity and specificity. For roll-out of colposcopy-based early detection sufficient qualified staff is not available. Several self-sampling device products have been proposed as alternative, but their usability in primary care needs to be proven. Implementation of an HPV-based self-sampling approach in a population-based setting in Indonesia was evaluated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Four self-sampling devices (2 urine, 2 swab) were applied in a primary care setting covering an entire district in Indonesia with Kulon Progo as pilot region. Cluster randomization was used for comparison of rural and urban areas. HPV-testing was done using standardized and validated PCR-techniques. HPV-positive women and a randomly selected HPV-negative control group underwent colposcopy, PAP smears and biopsies for CIN validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: In 21 primary care units 2056 women (30-55 y) were recruited. Three devices achieved sufficient technical validation (92.1 – 99.7% DNA detection rate). Participant’s test acceptance was 99.1%. HPV-prevalence was 2.6% (urine 2.4%, swab 2.8%). In 29.4% of HPV-positive women high-risk HPV-16/18 were detected. Colposcopy and morphological examination were refused by 3.0% of HPV-positive women and were technically invalid in 5.0%. Pathology revealed NILM in 55.8%, CIN I in 25.0% and CIN II+ in 3.8%. In the control group CIN I was found in 2.0%. This resulted in sensitivity for all CIN/CIN II+ of 27,4%/100,0%, specificity of 98,5%/97,7% with negative (NPV: 97,9%/100,0%) and positive predictive values (PPV: 34,1%/4,5%). Regression analysis confirmed high negative predictive impact of HPV-negativity in women \u0026gt;40 years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Under primary care setting self-sampling-based HPV-testing is accepted. Urine- and swab-based techniques can be applied if the test systems provide technically valid DNA-detection rates. The prevalence was very low and requires further comparison within Indonesia. High NPV of this approach supports its applicability as screening in LMICs. For high-risk lesions PPV is still low suggesting a combination with additional test that are mainly independent from the availability of qualified staff.\u003c/p\u003e","manuscriptTitle":"Population-based self-sampling under primary care conditions – a possible approach for cervical cancer screening in Indonesia (IndoCerCa study)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 11:03:13","doi":"10.21203/rs.3.rs-7429458/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-09T01:18:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-06T01:40:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327776717153007725473992079174930880693","date":"2025-12-30T12:14:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T13:49:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175067532560221473142115172942667136858","date":"2025-12-11T13:57:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185684419162882517219749897800320867092","date":"2025-10-13T08:08:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-04T06:39:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-26T08:54:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-26T08:50:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Health","date":"2025-08-21T22:48:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f170de9b-aeee-4ed7-a889-0faa208a15d3","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T20:23:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 11:03:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7429458","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7429458","identity":"rs-7429458","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}