Literature DB >> 30208597

Clinical Evaluation of INNO-LiPA HPV Genotyping EXTRA II Assay Using the VALGENT Framework.

Lan Xu1, Elizaveta Padalko2, Anja Oštrbenk3, Mario Poljak4, Marc Arbyn5.   

Abstract

In this diagnostic test validation study, we assessed the clinical accuracy and HPV genotyping performance of the INNO-LiPA HPV Genotyping Extra II (INNO-LiPA) within the VALGENT-3 framework. VALGENT is designed to assess the analytical and clinical performance of HPV tests with genotyping capacity. The VALGENT-3 panel comprised 1300 consecutive cervical cell specimens enriched with 300 samples with abnormal cytology obtained from women attending the Slovenian cervical cancer screening programme. The INNO-LiPA allows type-specific detection of 32 HPV types; however, for the clinical accuracy assessment, we considered it as high-risk (hr)HPV positive when at least one of the following HPV types was present: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59, and HPV68. Clinical accuracy for detection of cervical intraepithelial neoplasia grade 2 or worse (CIN2+) was compared between INNO-LiPA and Hybrid Capture 2 (HC2), which is a standard comparator test for HPV tests used in cervical cancer screening. In addition, hrHPV and type-specific detection HPV types were compared between INNO-LiPA and Linear Array HPV Genotyping Test (Linear Array). The prevalence of hrHPV determined by INNO-LiPA was 17.1% (95% CI, 15.0⁻19.2%) in the screening population. HrHPV testing with INNO-LiPA had a sensitivity for CIN2+ of 96.9% (95% CI, 92.1⁻99.1%) which was non-inferior to HC2 (relative sensitivity of 1.01; 95% CI, 0.97⁻1.04; pn.inf = 0.0002) and a specificity for ≤CIN1 of 85.3% (95% CI, 83.2⁻87.3%) which was inferior to HC2 (relative specificity of 0.95; 95% CI, 0.93⁻0.97; pn.inf = 0.9998). Genotyping agreement between INNO-LiPA and Linear Array was excellent for hrHPV, HPV16, HPV18, HPV35, HPV45, HPV58 and HPV59, but good or fair for other HPV types. To conclude, INNO-LiPA demonstrated non-inferior clinical sensitivity but lower specificity compared to HC2 in addition to excellent concordance compared to Linear Array for hrHPV and some genotypes.

Entities:  

Keywords:  HPV genotyping; Hybrid Capture 2; INNO-LiPA; Linear Array; VALGENT; cervical cancer; clinical validation; human papillomavirus

Mesh:

Substances:

Year:  2018        PMID: 30208597      PMCID: PMC6165258          DOI: 10.3390/ijms19092704

Source DB:  PubMed          Journal:  Int J Mol Sci        ISSN: 1422-0067            Impact factor:   5.923


1. Introduction

Over 200 human papillomavirus (HPV) types have been identified and classified based on their nucleotide sequences, with new HPV types being characterized at an increasing rate [1]. Among them, 12 high-risk HPV (hrHPV) types (HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58 and HPV59) are causally linked with cervical cancer and their immediate precursors [2]. In addition, eight more HPV types have been associated with some rare cases of cervical cancer (HPV26, HPV53, HPV66, HPV67, HPV68, HPV70, HPV73 and HPV82) [3]. The recognition of the strong etiological association between persistent hrHPV infection and cervical cancer has led to the development of novel HPV tests to enhance secondary prevention of the cervical cancer [4,5]. Furthermore, randomized controlled trials (RCTs) have demonstrated that HPV-based screening is more effective than cervical cytology in reducing the incidence of invasive cervical carcinoma in primary screening for cervical cancer for women aged 30 years or older [5,6]. Thus, a number of countries are currently in the process of switching from cervical cytology to HPV based primary screening for cervical cancer [7]. Many HPV tests are available on the market but only few have been clinically validated for use in primary screening settings [8]. The Hybrid Capture 2 assay (HC2; Qiagen, Hilden, Germany) [6,9,10,11] and GP5+/6+ PCR-based enzyme immunoassay (GP5+/6+-EIA; Diassay, Rijwijk, the Netherlands) [12,13,14] are HPV DNA assays that had been clinically validated for primary screening based on longitudinal evidence obtained from large RCTs. Therefore, HC2 and GP5+/6+-EIA are accepted as the standard comparator tests in evaluations of alternative HPV tests [15]. Several other HPV tests have been fully or partially validated and demonstrate non-inferior clinical sensitivity and specificity for detection of cervical intraepithelial neoplasia grade 2 or worse (CIN2+) compared to the standard comparator tests and high inter-and intra-laboratory reproducibility [15,16]. Majority of validated HPV tests target 13 or 14 hrHPV types in aggregate, but some have limited (partial genotyping for HPV16 and HPV18 only), extended (separate genotyping of HPV16, HPV18 and other hrHPV types) and full (type-specific genotyping of all included types) genotyping ability [16]. Since HPV16 and HPV18 are responsible for approximately 70% of cervical cancer, partial HPV genotyping for these two types is frequently used in the triage of HPV-positive women [17,18]. Although the usefulness of full genotyping of hrHPV types is not yet established, a recent study showed that, in addition to HPV16, HPV31 and HPV33 are more carcinogenic than other hrHPV types, suggesting that wider genotyping may also be clinically valuable [19]. INNO-LiPA HPV genotyping assay, based on the principle of reverse hybridization after highly sensitive PCR amplification with SPF10 primers, have been used for HPV genotyping over two decades [20,21]. During this timeframe, the original assay has undergone several modifications, resulting in a few different versions. The INNO-LiPA HPV Genotyping Extra II assay (INNO-LiPA; Fujirebio Europe, Ghent, Belgium) evaluated in the current study is the most recent assay launched by the company in 2015, targeting 32 types, four types more than the previous version. This new version contains genotype specific probes for more decisive genotyping results, an upgraded SPF10 primer set resulting in improved sensitivity (comparable for all hrHPV types), improved human DNA control primers and provides a ready-to-use amplification reagent [22]. In the present study, the VALidation of HPV GENotyping Tests (VALGENT) framework was used to evaluate the clinical accuracy of INNO-LiPA in comparison with HC2. For the first time, it was verified whether hrHPV testing with INNO-LiPA fulfills the minimal requirements for use in primary cervical cancer screening [15]. In addition, type-specific concordance was compared between the INNO-LiPA and the Linear Array HPV Genotyping Test (Linear Array; Roche Molecular Diagnostics, Branchburg, NJ, USA). HrHPV testing with the latter test was recently clinically validated through the VALGENT network as well and has been proposed as a standard analytical HPV genotyping comparator test to resolve discordant typing results of clinically validated HPV assays [23].

2. Results

The characteristics of the VALGENT-3 study population, including demographics, cytological and histological results have been described previously [23,24]. Of the 1600 samples analyzed by INNO-LiPA, four samples showed no signal for human HLA-DPB1 gene control line. These four samples were considered as invalid and therefore excluded for further analysis. Of the 1296 valid samples obtained from screening population, 17.1% women (221/1296) tested positive for the presence of any of the 13 hrHPV types by INNO-LiPA. The overall and type-specific prevalence of 13 hrHPV types in the total study population determined by INNO-LiPA is summarized in Table 1. The hrHPV prevalence was 15.2% in women with NILM (negative for intraepithelial lesion or malignancy) and increased to 42.8%, 69.0% and 86.0% in women diagnosed with ASC-US (atypical squamous cells of undetermined significance), LSIL (low-grade squamous intraepithelial lesion) and HSIL(high-grade squamous intraepithelial), respectively. The risk ratio (RR) of HSIL compared to women with NILM was highest (RR > 8.00) in women infected with in HPV16, HPV33, HPV18 and HPV45.
Table 1

Overall prevalence of hrHPV (aggregate of 13 types) and of individual hrHPV types detected by INNO-LiPA in the total study population according to baseline cytology.

HPV TypeHrHPV Prevalence (No. and %) by Cytology ResultsRatio Prevalence HSIL/NILM
NILM(N = 1234)ASC-US(N = 131)LSIL(N = 113)HSIL(N = 114)
13 hrHPV *187 (15.2%)56 (42.8%)78 (69.0%)98 (86.0%)5.7
HPV1632 (2.6%)12 (9.2%)27 (23.9%)56 (49.1%)18.9
HPV1812 (1.0%)4 (3.1%)9 (8.0%)10 (8.8%)8.8
HPV3154 (4.4%)22 (16.8%)19(16.8)23 (20.2%)4.6
HPV3311 (0.9%)5 (3.8%)9 (8.0%)11 (9.7%)10.8
HPV353 (0.2%)1 (0.8%)0 (0.0%)2 (0.9%)4.5
HPV3916 (1.3%)1 (0.8%)5 (4.4%)2 (1.8%)1.4
HPV456 (0.5%)5 (3.8%)4 (3.5%)5 (4.4%)8.8
HPV5131 (2.5%)4 (3.1%)9 (8.0%)5 (4.4%)1.8
HPV5227 (2.2%)10 (7.6%)11 (9.7%)7 (6.1%)2.8
HPV5611 (0.9%)2 (1.5%)7 (6.2%)5 (4.4%)4.9
HPV589 (0.7%)3 (2.3%)7 (6.2%)5 (4.4%)6.3
HPV5911 (0.9%)3 (2.3%)4 (3.5%)0 (0.0%)0
HPV6816 (1.3%)5 (3.8%)7 (6.2%)5 (4.4%)3.4

NILM, negative for intraepithelial lesion or malignancy; ASC-US, atypical squamous cells of undetermined significance; LSIL, low-grade squamous intraepithelial lesion; HSIL, high-grade squamous intraepithelial. * A positive hrHPV result represents detection of at least one of the 13 hrHPV types included in the HC2: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59 and HPV68. Women infected with multiple HPV types were counted only once.

2.1. Clinical Performance of the INNO-LiPA

The accuracy data for the INNO-LiPA and HC2 for the outcomes CIN2+, CIN3+ and ≤CIN1 are shown in Table 2 for the total study population and for women aged 30 years or older. When the whole study population was considered, INNO-LiPA detected 123 of 127 CIN2+ cases and 81 of 82 CIN3+ cases, which corresponds to a sensitivity of 96.9% (95% CI, 92.1–99.1) and 98.8% (93.4–100), respectively. The specificity for ≤CIN1 of INNO-LiPA (1034/1212) was 85.3% (95% CI, 83.2–87.3). Similar results were obtained for women aged 30 years or older.
Table 2

Sensitivity of INNO-LiPA and HC2 for detection of CIN2+ and CIN3+ and specificity of both assays for detection of ≤CIN1. Analysis was performed separately for the total study population and for women ≥30 years old.

Assay, Study Population and Clinical OutcomeSensitivitySpecificity
n/N%95% CIn/N%95% CI
INNO-LiPA a
Total study population
CIN2+123/12796.9(92.1–99.1)
CIN3+81/8298.8(93.4–100)
≤CIN1 1034/121285.3(83.2–87.3)
Women >30 years old
CIN2+95/9896.9(91.3–99.4)
CIN3+65/6698.5(91.8–100)
≤CIN1 887/100987.9(85.7–89.9)
HC2
Total study population
CIN2+122/12796.1(91.1–98.7)
CIN3+80/8297.6(91.5–99.7)
≤CIN1 1092/121290.1(88.3–91.8)
Women >30 years old
CIN2+94/9895.9(89.9–98.9)
CIN3+64/6697.0(89.5–99.6)
≤CIN1 935/100992.7(90.9–94.2)

a Positive INNO-LiPA results represents detection of at least one of the following 13 hrHPV types included in the HC2: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59 and HPV68. n, number of cases; N, total number of cases; CI, confidence interval.

The relative sensitivity of INNO-LiPA compared to HC2 was 1.01 (95% CI, 0.97–1.04; pmcn = 0.6547; pn.inf = 0.0002) for CIN2+ and 1.01 (95% CI, 0.97–1.06; pmcn = 0.5637; pn.inf = 0.001) for CIN3+. The relative specificity of INNO-LiPA for ≤CIN1 was 0.95 (95% CI, 0.93–0.97; pmcn = 0.0000; pn.inf = 0.0000). Similar results were obtained if the analysis was restricted to women ≥30 years (Table 3).
Table 3

Relative sensitivities for detection of CIN2+ and CIN3+ and relative specificity for detection of ≤CIN1 of INNO-LiPA versus HC2. Analysis was performed separately for the total study population and for women ≥30 years old.

INNO-LiPA vs. HC2Relative SensitivityRelative Specificity p mcn a p n.inf b
Total study population
CIN2+1.01 (0.97–1.04) 0.65470.0002
CIN3+1.01 (0.97–1.06) 0.56370.001
≤CIN1 0.95 (0.93–0.97)<0.0010.9998
Women > 30 years old
CIN2+1.01 (0.96–1.06) 0.65470.001
CIN3+1.02 (0.96–1.07) 0.56370.003
≤CIN1 0.95 (0.93–0.97)<0.0010.999

ap for the McNemar test for a difference between matched proportions and pmcn > 0.05 indicates that the sensitivity or specificity of the INNO-LiPA assay are not significantly different from that of the HC2. b p for the test for non-inferiority. A sensitivity threshold of at least 90% and a specificity threshold of at least 98% relative to that of the HC2 were applied in a non-inferiority score test. pn.inf < 0.05 means that the sensitivity or specificity of the INNO-LiPa is not significantly lower than that of the HC2.

2.2. Genotyping Agreement between INNO-LiPA and Linear Array

In the total study population, concordance between INNO-LiPA and Linear Array was assessed at type-specific level and overall for 13 hrHPV types (Table 4). Overall concordance of the two assays for 13 hrHPV types was 93.0% and the corresponding κ value was 0.805 (95% CI, 0.757–0.0854), indicating excellent agreement between INNO-LiPA and Linear Array. Similarly, the level of agreement was also excellent for detection of HPV16, HPV18, HPV35, HPV45, HPV58 and HPV59. However, for the identification of other individual types, level of agreement ranged from good to poor between the two assays (Table 4). In addition, INNO-LiPA detected more positive cases than Linear Array for all individual types common to both assays.
Table 4

Agreement (concordance and κ values) between the INNO-LiPA and the Linear Array for overall hrHPV positivity and for 29 individual HPV types common to both assays in the total study population.

HPV TypeI+/L+I+/L−I−/L+I−/L−Concordanceκ (95% CI) p mcn a
13 hrHPV b31810391166 93.0% 0.805 (0.757–0.854) <0.001
HPV161121621466 99.0% 0.920 (0.871–0.969) 0.001
HPV1831631556 99.4% 0.870 (0.822–0.920) 0.3173
HPV3168501141796.8%0.712 (0.664–0.759)<0.001
HPV3324131155899.2%0.770 (0.722–0.818)0.0013
HPV355001591 100.0% 1.000 (0.951–1.049) 1.0000
HPV391592157099.1%0.728 (0.680–0.777)0.0348
HPV4514601576 99.6% 0.822 (0.774–0.870) 0.0143
HPV5133161154698.9%0.790 (0.742–0.838)<0.001
HPV5230262153894.6%0.674 (0.633–0.714)0.8840
HPV561697156499.0%0.662 (0.613–0.712)0.6171
HPV5819501572 99.7% 0.882 (0.833–0.931) 0.0253
HPV5917221575 99.8% 0.894 (0.845–0.943) 1.0000
HPV687260156398.4%0.345 (0.308–0.382)<0.001
HPV26 c0001596 100.0% -1.0000
HPV5343231152998.5%0.774 (0.726–0.822)<0.001
HPV6629161155098.9%0.768 (0.720–0.816)<0.001
HPV7011100157599.4%0.685 (0.638–0.731)0.0016
HPV731972157099.4%0.788 (0.739–0.837)0.0956
HPV82541158699.7%0.665 (0.617–0.713)0.1797
HPV067141157499.1%0.479 (0.435–0.523)0.0008
HPV11230159199.8%0.571 (0.526–0.615)0.0833
HPV40140159199.8%0.333 (0.296–0.369)0.0455
HPV42359157999.1%0.296 (0.248–0.344)0.2850
HPV54101412156098.4%0.427 (0.378–0.476)0.6949
HPV6116176155798.6%0.575 (0.527–0.623)0.0218
HPV6215129156098.7%0.582 (0.533–0.632)0.5127
HPV67351158799.6%0.498 (0.452–0.543)0.1025
HPV81331158999.8%0.599 (0.551–0.647)0.3173
HPV83063158799.4%−0.003 (−0.049–0.044)0.3173

I+ = INNO-LiPA positive; I− = INNO-LiPA negative; L+ = Linear Array positive; L− = Linear Array negative. Color legend (adapted from Landis and Koch for the levels of agreement [25]): dark green (1.00 ≥ κ >0.80): excellent; light green (0.80 ≥ κ > 0.60): good; yellow (0.60 ≥ κ > 0.40): moderate; orange (0.40 ≥ κ > 0.20): fair; red (0.20 ≥ κ > 0.00): poor. a p for the McNemar test for a difference between matched proportions and pmcn < 0.05 indicates that the HPV positivity detected by INNO-LiPA is significantly different from that of the Linear Array. b 13 hrHPV types: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59 and HPV68. c No HPV26 positive cases detected by both assays, κ value not applicable.

3. Discussion

The INNO-LiPA provides full genotyping capability for 32 HPV types. For the purpose of this study, INNO-LiPA was considered positive if at least one of the 13 hrHPV types targeted by HC2 was detected. To the best of our knowledge, the INNO-LiPA has not been validated previously according to the international guidelines for evaluation of new HPV tests in primary cervical cancer screening settings. Here, we present the first study to evaluate the clinical performance of the INNO-LiPA compared to HC2 using samples from the VALGENT-3 panel. In the whole study population, the INNO-LiPA showed a sensitivity for the detection of CIN2+ and CIN3+ of 97% and 99%, respectively, which was similar to HC2. However, the clinical specificity for ≤CIN1 was only 85%, which was 5% (95% CI, 3–7%) lower than the comparator test. INNO-LiPA is a SPF10 PCR that targets a short highly conserved region in the L1 gene [21,26]. The small size of the amplicon makes the test analytically very sensitive. However, at the same time, discrimination of the individual types is challenging and complex and it is therefore not so surprising that the clinical specificity is lower compared to HPV tests targeting longer DNA sequences [27]. The small size of the amplicon makes INNO-LiPA particularly useful for testing of archived cell preparations or formaline-fixed-paraffin-embedded tissue blocks stored over long periods where parts of the viral genome can be fragmented [28]. INNO-LiPA provides for each HPV type a qualitative output, which is translated into a positive/negative result. The appreciation of presence or absence of blue lines is not quantifiable. Therefore, adaptation of the cut-off, which may allow a more optimal balance between clinical sensitivity and specificity, is in case of INNO-LiPA not possible. Excellent analytical agreement between INNO-LiPA and Linear Array was observed for 13 hrHPV types overall, HPV16, HPV18, HPV35, HPV45, HPV58 and HPV59. In addition, INNO-LiPA detected more positive cases than Linear Array for all individual HPV types that are common to both assays, with a positivity rate of hrHPV determined by INNO-LiPA statistically significantly higher than that determined by Linear Array (pmcn < 0.001) in the total study population. The significant difference of positivity rate for hrHPV with these two genotyping methods is consistent with the tests’ clinical performances with regard to relative specificity compared to HC2. In conclusion, in our study, INNO-LiPA exhibits lower clinical specificity; however, this is most likely due to detection of HPV infections with low concentrations and therefore can play an important role in evaluation of viral infection outcomes of vaccination trials and in monitoring the impact of HPV vaccination. Moreover, INNO-LiPA may be useful in epidemiological studies to investigate the prevalence and distribution of HPV types and in studies of the natural history of HPV infection at the type-specific level.

4. Materials and Methods

4.1. Clinical Specimens

The VALGENT framework is designed to assess the comparative analytical and clinical performance of HPV tests that offer limited to full genotyping capability [29]. VALGENT is iterative, using specimens collected in different countries. The first two VALGENT panels have been completed, using samples collected from Belgium [30,31,32] and Scotland [33,34,35,36]. The third study panel (VALGENT-3) was collated in Slovenia as previously described [11,23,24]. Briefly, 1300 consecutive cervical samples were collected from women who participated in the organised Slovenian national cervical cancer screening program between December 2009 and August 2010 (screening population). The study panel was enriched with 300 cytologically abnormal specimens collected between January 2014 and May 2015 (enrichment population). As required in the VALGENT protocol [29], the enrichment population included 100 women with atypical squamous cervical cells of undetermined significance (ASC-US), 100 women with low-grade squamous intraepithelial lesion (LSIL) and 100 women with high-grade squamous intraepithelial lesion (HSIL). The sample collection, aliquoting procedure and storage details have been described in detail in previous VALGENT-3 manuscripts [23,24]. Briefly, in July 2016, Ghent University (Ghent Belgium) received 1600 samples of extracted DNA. DNA was extracted from original samples collected into ThinPrep PreservCyt solution (Hologic, Marlborough, MA, USA). Prior to DNA extraction, 1 mL aliquot of original ThinPrep sample was centrifuged at 13,000× g for 15 m with supernatant being discarded and cellular pellet resuspended in 200 µL PBS buffer. DNA extraction was performed using QIAamp MinElute Media Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. Bound DNA was finally eluted with 50 µL of ATE buffer and stored at −70 °C prior to further testing. According to the manufacturer’s instructions, we have used 10 µL of extracted DNA for INNO-LiPA testing. Similarly, from the second aliquot of original ThinPrep DNA was extracted for Linear Array testing, where 50 µL of extracted DNA was used for further testing.

4.2. HPV Testing

4.2.1. INNO-LiPA HPV Genotyping Extra II

The INNO-LiPA is a line probe assay based on the principle of reverse hybridization for qualitative detection and identification of 32 different HPV types, including 13 hrHPV (HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59 and HPV68), 6 possible hrHPV (HPV26, HPV53, HPV66, HPV70, HPV73 and HPV82), 9 low-risk HPV (HPV6, HPV11, HPV40, HPV42, HPV43, HPV44, HPV54, HPV61 and HPV81) plus 4 other HPV genotypes (HPV62, HPV67, HPV83 and HPV89). INNO-LiPA uses the biotinylated consensus primers (SPF10) to amplify a 65-bp region within the L1 region of multiple alpha HPV types. The resulting biotinylated amplicons are then denatured and hybridized with specific oligonucleotide probes. A primer set for the amplification of the human HLA-DPB1 gene is included to monitor sample quality and extraction. The INNO-LiPA assay (sample incubation, stringent wash and color development) was performed fully automated using the AutoBlot 3000H (Bio-Rad Laboratories Inc., Hercules, CA, USA). Interpretation of the developed strips was done by scanning and automated interpretation using with the LiRAS for LiPA HPV software (Version 3.01, Fujirebio Europe, Ghent, Belgium). The test was performed in accordance with the manufacturer’s instructions.

4.2.2. HC2

HC2 detects 13 hrHPV types (HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59, and HPV68) and is accepted as a standard comparator test for the clinical validation of hrHPV DNA assays that may be used for primary cervical cancer screening [15]. For the purpose of the present study, hrHPV positivity for INNO-LiPA was defined as the presence of one or more of the 13 hrHPV targeted by HC2.

4.2.3. Linear Array

The Linear Array is an HPV test with full genotyping capacity, which detects 37 high- and low-risk HPV types (HPV6, HPV11, HPV16, HPV18, HPV26, HPV31, HPV33, HPV35, HPV39, HPV40, HPV42, HPV44, HPV45, HPV51, HPV52, HPV53, HPV54, HPV56, HPV58, HPV59, HPV61, HPV62, HPV64, HPV66, HPV67, HPV68, HPV69, HPV70, HPV71, HPV72, HPV73, HPV81, HPV82, HPV83, HPV84, HPV89, and IS39) that is frequently used in virological and epidemiological research. In the present study, Linear Array is used as a comparator test to evaluate the analytical genotyping accuracy of the INNO-LiPA.

4.3. Clinical Outcome and INNO-LiPA Performance Assessment

As described in previous VALGENT-3 reports [23,24], cytological assessment and referral of patients with abnormal cytology results to colposcopy were done according to the Slovenian national screening guidelines [37], which are in agreement with European guidelines [38]. Colposcopy-directed punch biopsies were obtained from suspicious areas for final histopathological assessment. Women with histologically confirmed CIN2+ results were considered as diseased subjects. Due to the fact that women with normal cytological results of negative for intraepithelial lesion or malignancy (NILM) were not referred to colposcopy verification in our study, we considered them as subjects without disease only if they had two or more consecutive NILM cytological results (at enrolment and at subsequent screening between 12 to 48 months later). We used this group of women to compute the clinical specificity for ≤CIN1. The clinical sensitivity and specificity of the INNO-LiPA for CIN2+ and CIN3+ were calculated. We compared the clinical accuracy of INNO-LiPA to HC2 for CIN2+ and CIN3+, using non-inferiority statistics with a relative sensitivity threshold of 90% and a relative specificity threshold of 98% [39]. The McNemar statistic was used in order to compare the differences between matched proportions [40]. For both statistics, the level of significance was set at 0.05. All analyses were performed using STATA version 14 (Manufacturer, College Station, TX, USA). Separate and consensus genotyping agreement for the types common to INNO-LiPA and Linear Array was assessed using κ [41] and McNemar statistics [40]. κ values from 0.0 to 0.20, 0.21 to 0.40, 0.41 to 0.60, 0.61 to 0.80 and 0.81 to 1.0 indicate poor, fair, moderate, good and excellent level of agreement between two assays. A McNemar p-value of <0.05 indicates significant discordance between genotyping results determined by the two assays.
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1.  Cross-sectional comparison of an automated hybrid capture 2 assay and the consensus GP5+/6+ PCR method in a population-based cervical screening program.

Authors:  A T Hesselink; N W J Bulkmans; J Berkhof; A T Lorincz; C J L M Meijer; P J F Snijders
Journal:  J Clin Microbiol       Date:  2006-10       Impact factor: 5.948

2.  Performance of a Cartridge-Based Assay for Detection of Clinically Significant Human Papillomavirus (HPV) Infection: Lessons from VALGENT (Validation of HPV Genotyping Tests).

Authors:  Kate Cuschieri; Daan Geraets; Jack Cuzick; Louise Cadman; Catherine Moore; Davy Vanden Broeck; Elisaveta Padalko; Wim Quint; Marc Arbyn
Journal:  J Clin Microbiol       Date:  2016-07-06       Impact factor: 5.948

Review 3.  Are 20 human papillomavirus types causing cervical cancer?

Authors:  Marc Arbyn; Massimo Tommasino; Christophe Depuydt; Joakim Dillner
Journal:  J Pathol       Date:  2014-12       Impact factor: 7.996

4.  Assessment of the Roche Linear Array HPV Genotyping Test within the VALGENT framework.

Authors:  Lan Xu; Anja Oštrbenk; Mario Poljak; Marc Arbyn
Journal:  J Clin Virol       Date:  2017-12-06       Impact factor: 3.168

5.  Short fragment polymerase chain reaction reverse hybridization line probe assay to detect and genotype a broad spectrum of human papillomavirus types. Clinical evaluation and follow-up.

Authors:  W J Melchers; J M Bakkers; J Wang; P C de Wilde; H Boonstra; W G Quint; A G Hanselaar
Journal:  Am J Pathol       Date:  1999-11       Impact factor: 4.307

6.  Development and clinical evaluation of a highly sensitive PCR-reverse hybridization line probe assay for detection and identification of anogenital human papillomavirus.

Authors:  B Kleter; L J van Doorn; L Schrauwen; A Molijn; S Sastrowijoto; J ter Schegget; J Lindeman; B ter Harmsel; M Burger; W Quint
Journal:  J Clin Microbiol       Date:  1999-08       Impact factor: 5.948

7.  International standardization and classification of human papillomavirus types.

Authors:  Davit Bzhalava; Carina Eklund; Joakim Dillner
Journal:  Virology       Date:  2015-01-09       Impact factor: 3.616

8.  Viral load of high-risk human papillomaviruses as reliable clinical predictor for the presence of cervical lesions.

Authors:  Markus Schmitt; Christophe Depuydt; Ina Benoy; Johannes Bogers; Jerome Antoine; Michael Pawlita; Marc Arbyn
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-01-18       Impact factor: 4.254

9.  HPV screening for cervical cancer in rural India.

Authors:  Rengaswamy Sankaranarayanan; Bhagwan M Nene; Surendra S Shastri; Kasturi Jayant; Richard Muwonge; Atul M Budukh; Sanjay Hingmire; Sylla G Malvi; Ranjit Thorat; Ashok Kothari; Roshan Chinoy; Rohini Kelkar; Shubhada Kane; Sangeetha Desai; Vijay R Keskar; Raghevendra Rajeshwarkar; Nandkumar Panse; Ketayun A Dinshaw
Journal:  N Engl J Med       Date:  2009-04-02       Impact factor: 91.245

10.  Need for expanded HPV genotyping for cervical screening.

Authors:  Jack Cuzick; Cosette Wheeler
Journal:  Papillomavirus Res       Date:  2016-06-01
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1.  Evaluation and Optimization of the Clinical Accuracy of Hybribio's 14 High-Risk HPV with 16/18 Genotyping Assay within the VALGENT-3 Framework.

Authors:  Lan Xu; Anja Oštrbenk Valenčak; Mario Poljak; Marc Arbyn
Journal:  J Clin Microbiol       Date:  2020-05-26       Impact factor: 5.948

2.  Prevalence and genotype-specific distribution of human papillomavirus in Burundi according to HIV status and urban or rural residence and its implications for control.

Authors:  Zacharie Ndizeye; Davy Vanden Broeck; Ramokone Lisbeth Lebelo; Johannes Bogers; Ina Benoy; Jean-Pierre Van Geertruyden
Journal:  PLoS One       Date:  2019-06-25       Impact factor: 3.240

3.  Identification by high-throughput sequencing of HPV variants and quasispecies that are untypeable by linear reverse blotting assay in cervical specimens.

Authors:  Lucie Molet; Delphine Girlich; Rémy A Bonnin; Alexis Proust; Jérôme Bouligand; Françoise Bachelerie; Sébastien Hantz; Claire Deback
Journal:  Papillomavirus Res       Date:  2019-07-05

4.  Clinical and Analytical Performance of the BD Onclarity HPV Assay with SurePath Screening Samples from the Danish Cervical Screening Program Using the VALGENT Framework.

Authors:  Jesper Hansen Bonde; Helle Pedersen; Wim Quint; Lan Xu; Marc Arbyn; Ditte Møller Ejegod
Journal:  J Clin Microbiol       Date:  2020-01-28       Impact factor: 5.948

5.  Comprehensive Cervical Cancer Prevention in Tanzania (CONCEPT) study: Cohort profile.

Authors:  Bariki Mchome; Patricia Swai; Chunsen Wu; Johnson Katanga; Crispin Kahesa; Rachel Manongi; Julius D Mwaiselage; Susanne Kjaer; Vibeke Rasch; Ditte Søndergaard Linde
Journal:  BMJ Open       Date:  2020-09-18       Impact factor: 2.692

6.  Frequent high-risk HPV co-infections excluding types 16 or 18 in cervical neoplasia in Guadeloupe.

Authors:  Stanie Gaete; Aviane Auguste; Bernard Bhakkan; Jessica Peruvien; Cecile Herrmann-Storck; Youri Socrier; Abdoulaye Diedhiou; Jacqueline Deloumeaux
Journal:  BMC Cancer       Date:  2021-03-16       Impact factor: 4.430

7.  Clinical validation of full genotyping CLART® HPV4S assay on SurePath and ThinPrep collected screening samples according to the international guidelines for human papillomavirus test requirements for cervical screening.

Authors:  Ditte Møller Ejegod; Camilla Lagheden; Ramya Bhatia; Helle Pedersen; Elia Alcañiz Boada; Karin Sundström; Javier Cortés; F Xavier Bosch Josë; Kate Cuschieri; Joakim Dillner; Jesper Bonde
Journal:  BMC Cancer       Date:  2020-05-06       Impact factor: 4.430

  7 in total

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