Pooling Alzheimer's disease clinical trial data to develop personalized medicine approaches is easier said than done: A proof-of-principle study and call to action.

With the advent of the first generation of disease-modifying treatments for Alzheimer's disease, it is clearer now more than ever that the field needs to move toward personalized medicine. Pooling data from past trials may help identify subgroups most likely to benefit from specific treatments and thus inform future trial design. In this perspective, we report on our effort to pool data from past Alzheimer's disease trials to identify patients most likely to respond to different treatments. We delineate challenges and hurdles, from our proof-of-principle study, for which we requested access to trial datasets from various pharmaceutical companies and encountered obstacles in the process of arranging data-sharing agreements through legal departments. Six phase I-III trials from three sponsors provided access to their data (total n = 3170), which included demographic information, vital signs, primary and secondary endpoints, and in a small subset, cerebrospinal fluid amyloid (n = 165, 5.2%) and tau (n = 212, 6.7%). Data could be analyzed only within specific data access platforms, limiting potential harmonization with data provided through other platforms. Limited overlap in terms of outcome measures, clinical and biological information hindered analyses. Thus, while it is a commendable advancement that (some) trials now allow researchers to study their data, we conclude that gaining access to past trial datasets is complicated, frustrating the field's communal effort to find the best treatments for the right individuals. We provide a plea to promote harmonization and open access to data, by urging trial sponsors and the academic research community alike to remove barriers to data access and improve collaboration through practicing open science and harmonizing outcome measures, to allow investigators to learn all there is to learn from past failures and successes. HIGHLIGHTS: Pooling data from past Alzheimer's disease clinical trials may help identify subgroups most likely to benefit from specific treatments and may help inform future trial design.Accessing past trial datasets is complicated, frustrating the field's communal effort to find the best treatments for the right individuals.We urge trial sponsors and the academic research community to remove data access barriers and improve collaboration through practicing open science and harmonizing outcome measures.

Predicting Cognitive Decline in Amyloid-Positive Patients With Mild Cognitive Impairment or Mild Dementia.

BACKGROUND AND OBJECTIVES: Cognitive decline rates in Alzheimer disease (AD) vary greatly. Disease-modifying treatments may alter cognitive decline trajectories, rendering their prediction increasingly relevant. We aimed to construct clinically applicable prediction models of cognitive decline in amyloid-positive patients with mild cognitive impairment (MCI) or mild dementia. METHODS: From the Amsterdam Dementia Cohort, we selected amyloid-positive participants with MCI or mild dementia and at least 2 longitudinal Mini-Mental State Examination (MMSE) measurements. Amyloid positivity was based on CSF AD biomarker concentrations or amyloid PET. We used linear mixed modeling to predict MMSE over time, describing trajectories using a cubic time curve and interactions between linear time and the baseline predictors age, sex, baseline MMSE, APOE ε4 dose, CSF ß-amyloid (Aß) 1-42 and pTau, and MRI total brain and hippocampal volume. Backward selection was used to reduce model complexity. These models can predict MMSE over follow-up or the time to an MMSE value. MCI and mild dementia were modeled separately. Internal 5-fold cross-validation was performed to calculate the explained variance (R2). RESULTS: In total, 961 participants were included (age 65 ± 7 years, 49% female), 310 had MCI (MMSE 26 ± 2) and 651 had mild dementia (MMSE 22 ± 4), with 4 ± 2 measurements over 2 (interquartile range 1-4) years. Cognitive decline rates increased over time for both MCI and mild dementia (model comparisons linear vs squared vs cubic time fit; p < 0.05 favoring a cubic fit). For MCI, backward selection retained age, sex, and CSF Aß1-42 and pTau concentrations as time-varying effects altering the MMSE trajectory. For mild dementia, retained time-varying effects were Aß1-42, age, APOE ε4, and baseline MMSE. R2 was 0.15 for the MCI model and 0.26 for mild dementia in internal cross-validation. A hypothetical patient with MCI, baseline MMSE 28, and CSF Aß1-42 of 925 pg/mL was predicted to reach an MMSE of 20 after 6.0 years (95% CI 5.4-6.7) and after 8.6 years with a hypothetical treatment reducing decline by 30%. DISCUSSION: We constructed models for MCI and mild dementia that predict MMSE over time. These models could inform patients about their potential cognitive trajectory and the remaining uncertainty and aid in conversations about individualized potential treatment effects.

DNA Methylation and P53 Immunohistochemistry as Prognostic Biomarkers for Vulvar Lichen Sclerosus.

Vulvar lichen sclerosus (LS) is an inflammatory dermatosis that can progress to human papillomavirus (HPV)-independent vulvar intraepithelial neoplasia (HPVi VIN) and vulvar squamous cell carcinoma (VSCC). Although LS has a much lower cancer risk compared with HPVi VIN (5% versus 50%, respectively), its incidence is significantly higher. Therefore, there is a clinical need to identify LS patients with an increased cancer risk. Our objective was to study the value of DNA methylation and p53 immunohistochemistry (IHC) as prognostic biomarkers for progression to cancer in patients with LS. Vulvar tissues from 236 patients were selected, including 75 LS and 68 HPVi VIN, both with and without cancer development, 32 VSCC, and 61 healthy vulvar controls. Samples were subjected to p53 IHC and DNA methylation analysis of a 3-gene marker panel containing ZNF582, SST, and miR124-2. Methylation levels and p53 IHC status (mutant or wild-type) were assessed and compared among all disease categories. Odds ratios were determined to identify whether the biomarkers were associated with progression to cancer in patients with LS. The highest methylation levels were found in HPVi VIN and VSCC, followed by LS and healthy vulvar controls. The largest heterogeneity in methylation levels was observed in LS cases. In fact, the 3-marker panel tested positive in 70% of LS, which progressed to VSCC versus only 17% of LS in patients without cancer development (P = .002). Also, mutant p53 IHC was observed more frequently in LS with progression to VSCC compared with nonprogressive LS cases (42% versus 3%, respectively, P = .001). Multivariable analysis identified a mutant p53 status as the only independent risk factor for cancer development in LS (odds ratio: 34.0, 95% CI: 1.4-807.4). In conclusion, DNA methylation testing and p53 IHC show strong potential as prognostic biomarkers for the identification of LS patients at high risk of progression to cancer.

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

BACKGROUND: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. METHODS: We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. RESULTS: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). CONCLUSION: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Low methylation marker levels among human papillomavirus-vaccinated women with cervical high-grade squamous intraepithelial lesions.

Cervical cancer screening programs, including triage tests, need redesigning as human papillomavirus (HPV)-vaccinated women are entering the programs. Methylation markers offer a potential solution to reduce false-positive rates by identifying clinically relevant cervical lesions with progressive potential. In a nested case-control study, 9242 women who received the three-dose HPV16/18-vaccine at ages 12-15 or 18 in a community-randomized trial were included. Subsequently, they were re-randomized for either frequent or infrequent cervical cancer screening trials. Over a 15-year post-vaccination follow-up until 2022, 17 high-grade squamous intraepithelial lesion (HSIL) and 15 low-grade (LSIL) cases were identified at the 25-year screening round, alongside 371 age and community-matched HPV16/18-vaccinated controls. Methylation analyses were performed on cervical samples collected at age 25, preceding histologically confirmed LSIL or HSIL diagnoses. DNA methylation of viral (HPV16/18/31/33) and host-cell genes (EPB41L3, FAM19A4, and miR124-2) was measured, along with HPV-genotyping. No HPV16/18 HSIL cases were observed. The predominant HPV-genotypes were HPV52 (29.4%), HPV59/HPV51/HPV58 (each 23.5%), and HPV33 (17.7%). Methylation levels were generally low, with no significant differences in mean methylation levels of viral or host-cell genes between the LSIL/HSIL and controls. However, a significant difference in methylation levels was found between HSIL cases and controls when considering a combination of viral genes and EPB41L3 (p value = .0001). HPV-vaccinated women with HSIL had HPV infections with uncommon HPV types that very rarely cause cancer and displayed low methylation levels. Further investigation is warranted to understand the likely regressive nature of HSIL among HPV-vaccinated women and its implications for management.

Incidence and Risk Factors for Recurrence and Progression of HPV-Independent Vulvar Intraepithelial Neoplasia.

OBJECTIVES: Human papillomavirus (HPV)-independent vulvar intraepithelial neoplasia (VIN) is a rare yet aggressive precursor lesion of vulvar cancer. Our objectives were to estimate its long-term incidence, the risk of recurrent disease and progression to vulvar cancer, and risk factors thereof. MATERIALS AND METHODS: Patients with HPV-independent VIN between 1991 and 2019 in a selected region were identified from the Dutch Nationwide Pathology Databank (Palga). Data were collected from the pathology reports. Crude and European age-standardized incidence rates were calculated for 10-year periods. Kaplan-Meier analyses were performed to determine the cumulative recurrence and cancer incidence, followed by Cox regression analyses to identify associated risk factors. RESULTS: A total of 114 patients were diagnosed with solitary HPV-independent VIN without prior or concurrent vulvar cancer. The European age-standardized incidence rate increased from 0.09 to 0.69 per 100,000 women-years between 1991-2010 and 2011-2019. A cumulative recurrence and cancer incidence of 29% and 46% were found after 8 and 13 years of follow-up, respectively. Nonradical surgery was identified as the only independent risk factor for recurrent HPV-independent VIN. Risk factors associated with progression to cancer were increasing age and a mutant p53 immunohistochemical staining pattern. CONCLUSIONS: The incidence of detected HPV-independent VIN has substantially increased the last decade and the subsequent recurrence and vulvar cancer risks are high. Although HPV-independent VIN may present as a wide morphologic spectrum, surgical treatment should aim for negative resection margins followed by close surveillance, especially for p53 mutant lesions.

Colposcopy Referral and CIN3+ Risk of Human Papillomavirus Genotyping Strategies in Cervical Cancer Screening.

BACKGROUND: High-risk human papillomavirus (hrHPV)-based cervical cancer screening in the Netherlands led to a substantial increase in number of colposcopy referrals and low-grade lesions detected. Genotyping strategies may be employed to lower the screening-related burden. METHODS: We evaluated 14 triage strategies with genotyping (HPV16/18 or HPV16/18/31/33/45/52/58) for hrHPV-positive borderlineormilddyskaryosis (BMD)ornormal cytology,usingdata from a population-based hrHPV-based screening trial with 5-year interval (POBASCAM). We considered colposcopy referral at baseline, after 6-month repeat cytology and after 5-year hrHPV testing. Performance was evaluated by one-round positive and negative predictive value (PPVandNPV) for CIN3+ and by two-roundcolposcopy referral rate. To identify efficient strategies, they were ordered by the one-round colposcopy referral rate. Adjacent strategies were compared by the marginal PPV for detecting one additional CIN3+ (mPPV). RESULTS: The most conservative strategy (repeat cytology after BMD and HPV16/18/31/33/45/52/58-positive normal cytology, next round otherwise) yielded an mPPV of 28%, NPV of 98.2%, and two-round colposcopy referral rate of 47.2%. Adding direct referral after BMD or genotype-positive BMD yielded an mPPV ≤ 8.2%, NPV ≥ 98.5% and an increase in colposcopy referral rate of 1.9% to 6.5%. Adding direct referral after HPV16/18-positive normal cytology yielded an mPPV ≤ 3.5%, NPV ≥ 99.5% and an increase in colposcopy referral rate of 13.9%. CONCLUSIONS: Direct colposcopy referral of women with BMD or normal cytology is unlikely to be efficient, but genotype-guided direct referral after BMD may be considered because the increase in colposcopies is limited. IMPACT: hrHPV screening programs can become very efficient when immediate colposcopy referral is limited to women at highest CIN3+ risk. See related In the Spotlight, p. 979.

Adaptive behavior assessed by Vineland-3 as comprehensive outcome measure in vanishing white matter.

OBJECTIVES: Investigate the results and usability of the Vineland-3 as an outcome measure in vanishing white matter patients. METHODS: A cross-sectional investigation of the Vineland-3 based on interviews with caregivers, the Health Utilities Index, and the modified Rankin Scale in 64 vanishing white matter patients. RESULTS: Adaptive behavior measured with the Vineland-3 is impaired in the vast majority of vanishing white matter patients and significantly impacts daily life. Typically, the daily living skills domain is most severely affected and the socialization domain is the least affected. Based on the metric properties and the clinical relevance, the standard scores for the daily living skills domain and Adaptive Behavior Composite have the best properties to be used as an outcome measure. INTERPRETATION: The Vineland-3 appears to be a useful outcome measure to explore and quantify complex cognitive, behavioral, and psychiatric impairments affecting daily functioning in vanishing white matter. Further research should address the longitudinal evaluation of this tool and its additional value to standard neuropsychological and clinical examination.