Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness.

In anticipation of potential future pandemics, we examined the challenges and opportunities presented by the COVID-19 outbreak. This analysis highlights how artificial intelligence (AI) and predictive models can support both patients and clinicians in managing subsequent infectious diseases, and how legislators and policymakers could support these efforts, to bring learning healthcare system (LHS) from guidelines to real-world implementation. This report chronicles the trajectory of the COVID-19 pandemic, emphasizing the diverse data sets generated throughout its course. We propose strategies for harnessing this data via AI and predictive modelling to enhance the functioning of LHS. The challenges faced by patients and healthcare systems around the world during this unprecedented crisis could have been mitigated with an informed and timely adoption of the three pillars of the LHS: Knowledge, Data and Practice. By harnessing AI and predictive analytics, we can develop tools that not only detect potential pandemic-prone diseases early on but also assist in patient management, provide decision support, offer treatment recommendations, deliver patient outcome triage, predict post-recovery long-term disease impacts, monitor viral mutations and variant emergence, and assess vaccine and treatment efficacy in real-time. A patient-centric approach remains paramount, ensuring patients are both informed and actively involved in disease mitigation strategies.

Performance of BD Onclarity HPV assay on FLOQSwabs vaginal self-samples.

This study assessed the accuracy of high-risk human papillomavirus testing of BD Onclarity HPV (Onclarity) assay on vaginal self-collected FLOQSwab versus cervical samples to ensure similar accuracy to detect cervical intraepithelial neoplasia. Testing was performed on two automated platforms, BD Viper LT and BD COR, to evaluate the effect of machine and using two vaginal self-samples to analyze the influence of collection, transport, and freezing-unfreezing on the results. A cervical sample and two self-samples were collected from 300 women. The first collected vaginal and the cervical sample were tested on BD Viper LT, and the second swab was frozen and subsequently tested on both automated systems. Test results on vaginal and cervical specimens were considered the index and comparator, respectively; colposcopy and histology were reference standards. Relative sensitivity for ≥CIN2 on vaginal samples analyzed versus the cervical sample was 1.01 (0.97-1.06), 1.01 (0.97-1.06), and 1.00 (0.95-1.05), for the first, second self-collected sample tested on BD VIPER LT, and second self-collected sample tested on BD COR, respectively. Relative specificity was 0.83 (0.73-0.94), 0.76 (0.67-0.87), and 0.82 (0.73-0.92) using the three different workflows. Cut-off optimization for human papillomavirus (HPV) positivity defined at Ct ≤38.3 for HPV16, ≤ 34.2 for HPV18, and ≤31.5 for all other types showed an increased relative specificity with similar sensitivity. No significant difference was observed between self-samples tested with the two platforms and between first- and second-collected swabs. Onclarity assay on FLOQSwab using both platforms showed similar sensitivity but lower specificity to detect ≥CIN2 compared to cervical samples. By cut-off optimization, non-inferior specificity could be reached. IMPORTANCE: Human papillomavirus (HPV) testing on self-collected vaginal samples has been shown to improve women's participation to cervical cancer screening programs, particularly in regions with limited access to health care. Nevertheless, the introduction of self-sampling in cervical cancer screening programs requires prior clinical validation of the HPV assay in combination with a self-sample collection device, including also the laboratory workflow and automation required for high-throughput testing in screening. In this study, the performance of BD Onclarity HPV on FLOQSwab-collected vaginal self-samples has been compared to clinician-taken liquid-based cytology samples, to detect high-grade cervical intraepithelial neoplasia using two high-throughput platforms, BD Viper LT and BD COR. The study findings have shown a similar performance of BD Onclarity on testing self-collected samples, confirming the validation of the proposed pre-analytical and analytical protocols for their use in cervical cancer screening programs based on self-collected vaginal samples.

Human Papillomavirus Genotype Richness and the Biodiversity of Squamous and Glandular Cervical Dysplasias: A Cross-Sectional Study.

The impact of multiple infections on the risk of cervical lesions is a subject of ongoing debate. This study aims to explore whether the richness of HPV genotype infections and the biodiversity of squamous and glandular cervical dysplasias could influence the progression of precancerous lesions. We conducted a cross-sectional analysis involving 469 women who attended the Colposcopy Unit at the European Institute of Oncology in Milan, Italy, from December 2006 to December 2014. HPV type richness was measured as the number of different genotypes per patient. We calculated the associations between richness and age, as well as histologic grade, along with Simpson's biodiversity index for cervical dysplasias. We observed significant inverse relationships between the richness of high-risk (HR) genotypes and both age (p = 0.007) and histologic grade (p < 0.001). Furthermore, as the histologic grade increased, the mean biodiversity index of cervical dysplasias decreased, with exceptions noted in cases of normal histology and adenocarcinoma in situ. Different histologic grades formed five clusters with distinct mean ages and mean biodiversity indices. These findings suggest that HPV genotype richness and the biodiversity of cervical dysplasias may play a crucial role in predicting the risk of high-grade cervical lesions, enabling personalized management of precancers.

The Editorial of the Special Issue "Diagnosis of Lower Genital Tract Disease".

A range of conditions involving the vulvovaginal and anal area, and those associated with human papillomavirus (HPV) infection, which can manifest as benign, pre-neoplastic, or neoplastic lesions, can be grouped into lower genital tract diseases [...].

Radiomics and Delta-Radiomics Signatures to Predict Response and Survival in Patients with Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors.

The aim of our study was to determine the potential role of CT-based radiomics in predicting treatment response and survival in patients with advanced NSCLC treated with immune checkpoint inhibitors. We retrospectively included 188 patients with NSCLC treated with PD-1/PD-L1 inhibitors from two independent centers. Radiomics analysis was performed on pre-treatment contrast-enhanced CT. A delta-radiomics analysis was also conducted on a subset of 160 patients who underwent a follow-up contrast-enhanced CT after 2 to 4 treatment cycles. Linear and random forest (RF) models were tested to predict response at 6 months and overall survival. Models based on clinical parameters only and combined clinical and radiomics models were also tested and compared to the radiomics and delta-radiomics models. The RF delta-radiomics model showed the best performance for response prediction with an AUC of 0.8 (95% CI: 0.65-0.95) on the external test dataset. The Cox regression delta-radiomics model was the most accurate at predicting survival with a concordance index of 0.68 (95% CI: 0.56-0.80) (p = 0.02). The baseline CT radiomics signatures did not show any significant results for treatment response prediction or survival. In conclusion, our results demonstrated the ability of a CT-based delta-radiomics signature to identify early on patients with NSCLC who were more likely to benefit from immunotherapy.

Tips and Tricks for Early Diagnosis of Cervico-Vaginal Involvement from Extramammary Paget's Disease of the Vulva: A Referral Center Experience.

Cervico-vaginal (CV) localization of extra-mammary Paget's disease (EMPD) of the vulva is extremely rare. In order to investigate the incidence risk and the pathognomonic clinical and pathological features of this condition, a retrospective analysis was conducted including 94 women treated for vulvar EMPD at the European Institute of Oncology, Milan, Italy, from October 1997 to May 2020. Overall nine patients developed CV involvement from EMPD, with a cumulative incidence of 2.5% (95% CI: 0.5-8.0%) at 5 years, 6.5% (95% CI: 1.9-15.1%) at 10 years and 14.0% (95% CI: 4.8-27.8%) at 15 years, respectively. All cases except one were firstly detected by abnormal glandular cytology. None reported vaginal bleeding or other suspicious symptoms. The colposcopic findings were heterogeneous and could sometimes be misdiagnosed. Cervical and/or vaginal biopsies were always performed for histopathological diagnosis by identification of Paget cells in the epithelium or stroma. Most patients developed invasive EMPD (5/9) of the cervix and/or vagina and underwent hysterectomy with partial or total colpectomy. CV involvement from EMPD should not be underestimated in women with a long-standing history of vulvar Paget's disease. Liquid-based cytology with immunocytochemistry represents a valuable tool for early diagnosis and should be routinely performed during the required lifelong follow-up.

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often requiring further investigations. Deep learning (DL) - a machine learning technique designed to mimic human neuronal interactions- has shown promise in the field of medical imaging analysis for different purposes, including segmentation and classification of lesions. In this study, we aim to develop a DL algorithm that can classify areas of increased uptake on bone scintigraphy scans. METHODS: We collected 2365 BS from three European medical centres. The model was trained and validated on 1203 and 164 BS scans respectively. Furthermore we evaluated its performance on an external testing set composed of 998 BS scans. We further aimed to enhance the explainability of our developed algorithm, using activation maps. We compared the performance of our algorithm to that of 6 nuclear medicine physicians. RESULTS: The developed DL based algorithm is able to detect MBD on BSs, with high specificity and sensitivity (0.80 and 0.82 respectively on the external test set), in a shorter time compared to the nuclear medicine physicians (2.5 min for AI and 30 min for nuclear medicine physicians to classify 134 BSs). Further prospective validation is required before the algorithm can be used in the clinic.

Which Risk Factors and Colposcopic Patterns Are Predictive for High-Grade VAIN? A Retrospective Analysis.

Colposcopic patterns of Vaginal Intraepithelial Neoplasia (VAIN) are not definitively related to histological grade. The aim of the present study was to investigate any correlation between clinical and colposcopic features and the development of high-grade VAIN. Two hundred and fifty-five women diagnosed with VAIN (52 VAIN1, 55 VAIN2 and 148 VAIN3) at the European Institute of Oncology, Milan, Italy, from January 2000 to June 2022, were selected for a retrospective analysis. Multivariate logistic regression was performed to estimate the association of risk factors and colposcopic patterns with VAIN grade. Smoking was associated with the development of VAIN (34.1%, p = 0.01). Most women diagnosed with VAIN3 (45.3%, p = 0.02) had a previous history of hysterectomy for CIN2+. At multivariate analysis, colposcopic grade G2 (OR = 20.4, 95%CI: 6.67−61.4, p < 0.001), papillary lesion (OR = 4.33, 95%CI: 1.79−10.5, p = 0.001) and vascularity (OR = 14.4, 95%CI: 1.86−112, p = 0.01) were significantly associated with a greater risk of VAIN3. The risk of high-grade VAIN should not be underestimated in women with a history of smoking and previous hysterectomy for CIN2+, especially when colposcopic findings reveal vaginal lesions characterized by grade 2, papillary and vascular patterns. Accurate diagnosis is crucial for an optimal personalized management, based on risk factors, colposcopic patterns and histologic grade of VAIN.

Evaluation of BD Onclarity™ HPV Assay on Self-Collected Vaginal and First-Void Urine Samples as Compared to Clinician-Collected Cervical Samples: A Pilot Study.

The accuracy of available HPV molecular assays on self-samples needs to be evaluated as compared to clinician-collected samples. This pilot study aimed to investigate the BD Onclarity™ HPV assay on vaginal and first-void urine samples. Sixty-four women referred to colposcopy for cervical dysplasia performed a vaginal self-collection and provided a first-void urine sample, after informed consent. A cervical specimen was collected during the clinician examination. All samples were tested using BD Onclarity™ HPV assay on the BD Viper™ LT System. Overall positive agreement (OPA) between cervical and self-sample results was evaluated using Cohen's kappa value (κ). Using a clinical cut-off of 38.3 Ct for HPV 16 and 34.2 Ct for other HR genotypes, compared to cervical sample, the self-collected vaginal sample OPA was 85.9%, and κ = 0.699. Without a clinical cut-off, the OPA was 95.3%, and the κ = 0.890. Data obtained comparing cervical and urine samples showed an OPA of 87.5% with a κ = 0.79 using a clinical cut-off, and an OPA of 90.6% with a κ = 0.776 without a clinical cut-off. Data showed a substantial agreement between both self-collected and clinician-collected samples. A specific clinical cut-off analysis should be considered based on type of sample analysed.

HPV Tests Comparison in the Detection and Follow-Up after Surgical Treatment of CIN2+ Lesions.

BACKGROUND: HPV tests differ for technology, targets, and information on genotyping of high risk (HR) HPV. In this study, we evaluated the performance of 6 HPV DNA tests and one mRNA test in the detection of cervical intraepithelial lesions (CIN) and as a test-of-cure in the follow-up after surgical conservative treatment. METHODS: One hundred seventy-two women referred to the European Institute of Oncology, Milan, for surgical treatment of pre-neoplastic cervical lesions, were enrolled in this study (IEO S544) from January 2011 to June 2015. For all women, a cervical sample was taken before treatment (baseline) and at the first follow-up visit (range 3 to 9 months): on these samples Qiagen Hybrid Capture 2 (HC2), Roche Linear Array HPV Test (Linear Array), Roche Cobas 4800 HPV test (Cobas), Abbott RealTime High Risk HPV test (RT), BD Onclarity HPV assay (Onclarity), Seegene Anyplex II HPV HR Detection (Anyplex), and Hologic Aptima HPV Assay (Aptima) histology and cytology were performed at baseline, and the same tests and cytology were performed at follow-up. RESULTS: At baseline 158/172 (92%), histologies were CIN2+, and 150/172 (87%) women were recruited at follow-up. Assuming HC2 as a comparator, the concordance of HPV tests ranges from 91% to 95% at baseline and from 76% to 100% at follow-up (PABAK ranging from 0.81 to 0.90 at baseline and PABAK ranging from 0.53 to 1 at follow-up). All HPV showed a very good sensitivity in CIN2+ detection at baseline, more than 92%, and a very good specificity at follow-up, more than 89%. CONCLUSIONS: HPV tests showed a good concordance with HC2 and a very good and comparable sensitivity in CIN2+ detection. Hence, an HPV test represents a valid option as test-of-cure in order to monitor patients treated for CIN2+ lesions during follow-up.

New Analytical Approach for the Alignment of Different HE4 Automated Immunometric Systems: An Italian Multicentric Study.

Human epididymal secretory protein 4 (HE4) elevation has been studied as a crucial biomarker for malignant gynecological cancer, such us ovarian cancer (OC). However, there are conflicting reports regarding the optimal HE4 cut-off. Thus, the goal of this study was to develop an analytical approach to harmonize HE4 values obtained with different laboratory resources. To this regard, six highly qualified Italian laboratories, using different analytical platforms (Abbott Alinity I, Fujirebio Lumipulse G1200 and G600, Roche Cobas 601 and Abbott Architett), have joined this project. In the first step of our study, a common reference calibration curve (designed through progressive HE4 dilutions) was tested by all members attending the workshop. This first evaluation underlined the presence of analytical bias in different devices. Next, following bias correction, we started to analyze biomarkers values collected in a common database (1509 patients). A two-sided p-value < 0.05 was considered statistically significant. In post-menopausal women stratified between those with malignant gynecological diseases vs. non-malignant gynecological diseases and healthy women, dichotomous HE4 showed a significantly better accuracy than dichotomous Ca125 (AUC 0.81 vs. 0.74, p = 0.001 for age ≤ 60; AUC 0.78 vs. 0.72, p = 0.024 for age > 60). Still, in post-menopausal status, similar results were confirmed in patients with malignant gynecological diseases vs. patients with benign gynecological diseases, both under and over 60 years (AUC 0.79 vs. 0.73, p = 0.006; AUC 0.76 vs. 0.71, p = 0.036, respectively). Interestingly, in pre-menopausal status women over 40 years, HE4 showed a higher accuracy than Ca125 (AUC 0.73 vs. 0.66, p = 0.027), thus opening new perspective for the clinical management of fertile patients with malignant neoplasms, such as ovarian cancer. In summary, this model hinted at a new approach for identifying the optimal cut-off to align data detected with different HE4 diagnostic tools.

A review in radiomics: Making personalized medicine a reality via routine imaging.

Radiomics is the quantitative analysis of standard-of-care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can be performed by extracting hand-crafted radiomics features or via deep learning algorithms. Radiomics has evolved tremendously in the last decade, becoming a bridge between imaging and precision medicine. Radiomics exploits sophisticated image analysis tools coupled with statistical elaboration to extract the wealth of information hidden inside medical images, such as computed tomography (CT), magnetic resonance (MR), and/or Positron emission tomography (PET) scans, routinely performed in the everyday clinical practice. Many efforts have been devoted in recent years to the standardization and validation of radiomics approaches, to demonstrate their usefulness and robustness beyond any reasonable doubts. However, the booming of publications and commercial applications of radiomics approaches warrant caution and proper understanding of all the factors involved to avoid "scientific pollution" and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decision-making, from oncology and respiratory medicine to pharmacological and genotyping studies.

The Potential Impact of High-Risk Human Papillomavirus-Negative Cervical Intraepithelial Neoplasia 2+ on Primary Human Papillomavirus Screening.

OBJECTIVES: To investigate the prevalence of high-risk human papillomavirus (HPV)-negative cervical intraepithelial neoplasia (CIN) and invasive cervical carcinoma (ICC) and to analyze the distribution of other genotypes in this subset. METHODS: In total, 431 women who underwent excisional surgical treatment for CIN or ICC at the European Institute of Oncology, Milan, Italy, from January 2016 to December 2017 were retrospectively analyzed. The Linear Array HPV genotyping test (Roche Diagnostics) was performed on a postaliquot from high-risk-HPV-negative liquid-based cervical specimens, when available. Patient characteristics and the prevalence of high-risk-HPV-negative CIN grade 2 or worse (CIN2+) were tabulated. We used t tests to compare age between high-risk-HPV-positive and high-risk-HPV-negative patients. RESULTS: Overall, 8.9% of CIN2+ and 7.5% of ICC cases were high-risk HPV negative. There was no age difference between high-risk-HPV-negative CIN2+ women (mean [SD], 41.3 [8.7] years) and high-risk-HPV-positive women (mean [SD], 39.5 [9.0] years) (P = .28). The Linear Array result was available in 22 cases. Most high-risk-HPV-negative patients were positive for a single other genotype infection (32.6%). HPV 73 was the most prevalent genotype, followed by HPV 53 and HPV 84. HPV 26 was detected in 1 case of ICC. CONCLUSIONS: Our results showed a not-negligible proportion of high-risk-HPV-negative CIN2+, suggesting that cotesting would not miss these cases.

Human Papillomavirus Same Genotype Persistence and Risk of Cervical Intraepithelial Neoplasia2+ Recurrence.

To evaluate the significance of HPV persistence as a predictor for the development of CIN2+ recurrence and the impact of multiple genotypes and of HPV 16/18 on recurrence risk. A prospective cohort observational study was carried out at the European Institute of Oncology, Milan, Italy, from December 2006 to December 2014. A total of 408 women surgically treated by excisional procedure for pre-neoplastic and neoplastic cervical lesions were enrolled. HPV test was performed at baseline and at first follow-up visit planned at 6 ± 3 months after treatment. Two-year cumulative incidences for relapse were estimated and compared by the Gray's test. Overall, 96 (23.5%) patients were persistent for at least one genotype at three to nine months from baseline and 21 (5.1%) patients relapsed. The two-year cumulative relapse incidence was higher in HPV persistent patients compared to not-persistent (CIF = 27.6%, 95% CI: 16.2-40.2% versus CIF = 1.7%, 95% CI: 0.3-5.8%, p < 0.001), in women with persistent multiple infections (CIF = 27.2%, 95% CI: 7.3-52.3%, p < 0.001), and with the persistence of at least one genotype between 16 and 18, irrespective of the presence of other HR genotypes (CIF = 32.7%, 95% CI: 17.9-48.3%, p < 0.001), but not significantly different from women positive for single infections or any other HR genotype, but not for 16 and 18. The risk of CIN2+ recurrence should not be underestimated when same HPV genotype infection persists after treatment.

Privacy preserving distributed learning classifiers - Sequential learning with small sets of data.

BACKGROUND: Artificial intelligence (AI) typically requires a significant amount of high-quality data to build reliable models, where gathering enough data within a single institution can be particularly challenging. In this study we investigated the impact of using sequential learning to exploit very small, siloed sets of clinical and imaging data to train AI models. Furthermore, we evaluated the capacity of such models to achieve equivalent performance when compared to models trained with the same data over a single centralized database. METHODS: We propose a privacy preserving distributed learning framework, learning sequentially from each dataset. The framework is applied to three machine learning algorithms: Logistic Regression, Support Vector Machines (SVM), and Perceptron. The models were evaluated using four open-source datasets (Breast cancer, Indian liver, NSCLC-Radiomics dataset, and Stage III NSCLC). FINDINGS: The proposed framework ensured a comparable predictive performance against a centralized learning approach. Pairwise DeLong tests showed no significant difference between the compared pairs for each dataset. INTERPRETATION: Distributed learning contributes to preserve medical data privacy. We foresee this technology will increase the number of collaborative opportunities to develop robust AI, becoming the default solution in scenarios where collecting enough data from a single reliable source is logistically impossible. Distributed sequential learning provides privacy persevering means for institutions with small but clinically valuable datasets to collaboratively train predictive AI while preserving the privacy of their patients. Such models perform similarly to models that are built on a larger central dataset.

Radiomics in Lung Diseases Imaging: State-of-the-Art for Clinicians.

Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50 years. As modern medicine is evolving towards precision medicine, offering personalized patient care and treatment, the requirement for robust imaging biomarkers has gradually increased. Radiomics, a specific method generating high-throughput extraction of a tremendous amount of quantitative imaging data using data-characterization algorithms, has shown great potential in individuating imaging biomarkers. Radiomic analysis can be implemented through the following two methods: hand-crafted radiomic features extraction or deep learning algorithm. Its application in lung diseases can be used in clinical decision support systems, regarding its ability to develop descriptive and predictive models in many respiratory pathologies. The aim of this article is to review the recent literature on the topic, and briefly summarize the interest of radiomics in chest Computed Tomography (CT) and its pertinence in the field of pulmonary diseases, from a clinician's perspective.

Onclarity Performance in Human Papillomavirus DNA Detection in Formalin-Fixed Paraffin-Embedded Cervical Samples.

OBJECTIVES: Diagnosis of HPV infection is usually performed from cervical liquid-based cytology specimens (LBC), but these often contain a large amount of human papillomavirus (HPV) genotypes, most of which might cause transient infections. The aim of the study was to evaluate the performance of BD Onclarity HPV test genotyping method on formalin-fixed, paraffin-embedded (FFPE) cervical specimens compared with genotyping results from LBC. MATERIALS AND METHODS: Formalin-fixed, paraffin-embedded specimens from women surgically treated for cervical intraepithelial lesions (CINs) at the European Institute of Oncology, Milan, from September 2012 to June 2013 were retrieved from the archives of the Department of Pathology of the European Institute of Oncology. The FFPE and LBC specimens were genotyped using the same extended genotyping Onclarity assay. RESULTS: We collected 99 samples (26 CIN 1, 30 CIN 2, and 43 CIN 3+), but 15 were excluded from the analysis: these 84 samples show an overall agreement of 89% for HPV status between FFPE Onclarity samples versus LBC samples. The FFPE and LBC samples showed identical genotype in 75% samples, compatible genotype (at least 1 of the genotypes detected in LBC sample was found in the tissue sample) in 14% specimens, and discrepant genotype in 11% samples. CONCLUSIONS: Our data demonstrate a very good concordance between HPV genotypes found in cytological and tissue samples, suggesting that the Onclarity method could also be used to detect HPV in tissue samples and that the HPV genotype detected in FFPE samples is one of the HPV detected in cytological samples, supporting the thesis that one lesion is caused by one HPV genotype.

Anyplex II HPV test in detection and follow-up after surgical treatment of CIN2+ lesions.

Human papillomavirus (HPV) tests differ for technology, targets, and information on the genotype and viral load. In this study, we evaluated the performance of the Seegene Anyplex II HPV HR (Anyplex) assay in the detection of cervical intraepithelial lesions (CIN) and as a test-of-cure in the follow-up after surgical treatment. One hundred and sixty-seven women referred to the European Institute of Oncology, Milan, for surgical treatment of CIN2+ were enrolled. A cervical sample was taken before treatment and at the first follow-up visit: on these samples, Qiagen Hybrid Capture 2 (HC2), Roche Linear Array HPV Test (Linear Array), cytology and histology were performed at baseline, HC2, and cytology at follow-up. Anyplex genotyping HPV test was performed on a post aliquot from liquid-based cytology specimens when available. The concordance between Anyplex and HC2 was 93.6% at baseline and 76.7% at follow-up (3-9 months after treatment), respectively. The concordance between Anyplex and Linear Array was evaluable only at baseline (92.9%). No recurrence occurred in women without the persistence of the same genotype at follow-up. Seven women relapsed: six had persistence of the same genotypes (five HPV16, one HPV33, and one HPV39), while one tested negative not only with Anyplex but also with HC2 for the persistence of low-risk genotype infection (HPV73 only detected by Linear Array). Anyplex test represents a valid option for HPV detection and genotyping in order to stratify women at risk of high-grade lesions at baseline and to monitor patients treated for CIN2+ lesions during follow-up.

Human Papillomavirus Same Genotype Persistence and Risk: A Systematic Review.

OBJECTIVE: The aim of the study was to examine whether high-grade cervical intraepithelial neoplasia (CIN) was more closely associated with human papillomavirus (HPV) same-genotype persistence (SGTP) versus clearance of prior infection with a subsequent infection by a new genotype (genotype switch [GS]), clearance of HPV infection, or acquisition of a new HPV infection after a negative infection status, during a follow-up testing subsequent to abnormal screening results. MATERIALS AND METHODS: MEDLINE, Cochrane Library, Health Technology Assessment, and clinicaltrials.gov were searched from January 2000 to July 2019 for prospective controlled trials and observational studies of women and retrospective studies using HPV assays with extended- or full-genotype reporting. The primary outcome was high-grade CIN after at least 2 rounds of testing. Overall quality of evidence for the risk estimate outcomes was assessed. Of the 830 identified abstracts, 66 full-text articles were reviewed, and 7 studies were included in the synthesis. The study protocol was registered with the PROSPERO International Prospective Register of Systematic Reviews (CRD42018091093). RESULTS: Continued HPV-positive women falls in 2 equally large groups: SGTP and GS. Sensitivity, positive predictive value, and positive likelihood ratio of SGTP were significantly higher than for GS. Human papillomavirus genotypes may be ranked into 3 tiers (immediate colposcopy, follow-up testing, return to routine screening), according to associated risk of persistence for high-grade CIN and to prevailing clinical action thresholds. CONCLUSIONS: There is moderately high-quality evidence to support the clinical utility of SGTP to improve risk discrimination for high-grade CIN compared with qualitative HPV testing without genotype-specific information.

Do Aptamers Always Bind? The Need for a Multifaceted Analytical Approach When Demonstrating Binding Affinity between Aptamer and Low Molecular Weight Compounds.

In this manuscript, we compare different analytical methodologies to validate or disprove the binding capabilities of aptamer sequences. This was prompted by the lack of a universally accepted and robust quality control protocol for the characterization of aptamer performances coupled with the observation of independent yet inconsistent data sets in the literature. As an example, we chose three aptamers with a reported affinity in the nanomolar range for ampicillin, a ß-lactam antibiotic, used as biorecognition elements in several detection strategies described in the literature. Application of a well-known colorimetric assay based on aggregation of gold nanoparticles (AuNPs) yielded conflicting results with respect to the original report. Therefore, ampicillin binding was evaluated in solution using isothermal titration calorimetry (ITC), native nano-electrospray ionization mass spectrometry (native nESI-MS), and 1H-nuclear magnetic resonance spectroscopy (1H NMR). By coupling the thermodynamic data obtained with ITC with the structural information on the binding event given by native nESI-MS and 1H NMR we could verify that none of the ampicillin aptamers show any specific binding with their intended target. The effect of AuNPs on the binding event was studied by both ITC and 1H NMR, again without providing positive evidence of ampicillin binding. To validate the performance of our analytical approach, we investigated two well-characterized aptamers for cocaine/quinine (MN4), chosen for its nanomolar range affinity, and l-argininamide (1OLD) to show the versatility of our approach. The results clearly indicate the need for a multifaceted analytical approach, to unequivocally establish the actual detection potential and performance of aptamers aimed at small organic molecules.