Salivary and lacrimal dysfunction after radioactive iodine for differentiated thyroid cancer: American Head and Neck Society Endocrine Surgery Section and Salivary Gland Section joint multidisciplinary clinical consensus statement of otolaryngology, ophthalmology, nuclear medicine and endocrinology

BackgroundPostoperative radioactive iodine (RAI) administration is widely utilized in patients with differentiated thyroid cancer. While beneficial in select patients, it is critical to recognize the potential negative sequelae of this treatment. The prevention, diagnosis, and management of the salivary and lacrimal complications of RAI exposure are addressed in this consensus statement.MethodsA multidisciplinary panel of experts was convened under the auspices of the American Head and Neck Society Endocrine Surgery and Salivary Gland Sections. Following a comprehensive literature review to assess the current best evidence, this group developed six relevant consensus recommendations.ResultsConsensus recommendations on RAI were made in the areas of patient assessment, optimal utilization, complication prevention, and complication management.ConclusionSalivary and lacrimal complications secondary to RAI exposure are common and need to be weighed when considering its use. The recommendations included in this statement provide direction for approaches to minimize and manage these complications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163491/2/hed26417.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163491/1/hed26417_am.pd

Rapid Identification of Emerging Pathogens: Coronavirus

New surveillance approach can analyze >900 polymerase chain reactions per day

Common genetic variants in the CLDN2 and PRSS1-PRSS2 loci alter risk for alcohol-related and sporadic pancreatitis

Pancreatitis is a complex, progressively destructive inflammatory disorder. Alcohol was long thought to be the primary causative agent, but genetic contributions have been of interest since the discovery that rare PRSS1, CFTR, and SPINK1 variants were associated with pancreatitis risk. We now report two significant genome-wide associations identified and replicated at PRSS1-PRSS2 (1×10-12) and x-linked CLDN2 (p < 1×10-21) through a two-stage genome-wide study (Stage 1, 676 cases and 4507 controls; Stage 2, 910 cases and 4170 controls). The PRSS1 variant affects susceptibility by altering expression of the primary trypsinogen gene. The CLDN2 risk allele is associated with atypical localization of claudin-2 in pancreatic acinar cells. The homozygous (or hemizygous male) CLDN2 genotype confers the greatest risk, and its alleles interact with alcohol consumption to amplify risk. These results could partially explain the high frequency of alcohol-related pancreatitis in men – male hemizygous frequency is 0.26, female homozygote is 0.07

Paraganglioma of the Recurrent Laryngeal Nerve

Background/Objective: Paragangliomas are rare neuroendocrine tumors that primarily arise in the adrenal gland. Head and neck paragangliomas comprise approximately 3% of all extra-adrenal paragangliomas, with a majority of those being found in the carotid body. Recurrent laryngeal nerve paragangliomas are exceedingly rare, with only 2 reported cases found in literature review. Here, we will present the third. Case Report: The patient is a 46-year-old woman with a history of a right thyroid nodule that had been previously biopsied benign with “paucity of diagnostic material.” Neck ultrasonography revealed a 7.4 cm nodule that demonstrated interval growth over a 2-year period, so it was recommended to proceed with right thyroid lobectomy and isthmusectomy. During resection, the recurrent laryngeal nerve appeared to “disappear” into the nodule, and it was resected along with the nodule to ensure proper margins. The nerve was reconstructed with an ansa cervicalis interposition graft, and the nodule was sent to pathology. Pathology revealed that the nodule was a 4.8 cm paraganglioma of the recurrent laryngeal nerve. Discussion: Paragangliomas of the head and neck are exceedingly rare. In patients who present with symptoms of dysphagia or dysphonia, further workup, including laryngoscopy and magnetic resonance imaging, could potentially identify and allow for appropriate planning for surgical resection. Conclusion: In rare cases, consideration of paraganglioma as part of the differential for thyroid nodules may assist with planning of surgery but will unlikely alter treatment

Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BackgroundIdentification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by histopathological examination of tissue following surgical resection. Reliance on histopathological evaluation requires patients to undergo surgery to obtain a diagnosis despite most being non-cancerous. It is highly desirable to avoid surgery and to provide accurate classification of benignity versus malignancy from FNAB preoperatively. In our first-generation algorithm, Gene Expression Classifier (GEC), we achieved this goal by using machine learning (ML) on gene expression features. The classifier is sensitive, but not specific due in part to the presence of non-neoplastic benign Hürthle cells in many FNAB.ResultsWe sought to overcome this low-specificity limitation by expanding the feature set for ML using next-generation whole transcriptome RNA sequencing and called the improved algorithm the Genomic Sequencing Classifier (GSC). The Hürthle identification leverages mitochondrial expression and we developed novel feature extraction mechanisms to measure chromosomal and genomic level loss-of-heterozygosity (LOH) for the algorithm. Additionally, we developed a multi-layered system of cascading classifiers to sequentially triage Hürthle cell-containing FNAB, including: 1. presence of Hürthle cells, 2. presence of neoplastic Hürthle cells, and 3. presence of benign Hürthle cells. The final Hürthle cell Index utilizes 1048 nuclear and mitochondrial genes; and Hürthle cell Neoplasm Index leverages LOH features as well as 2041 genes. Both indices are Support Vector Machine (SVM) based. The third classifier, the GSC Benign/Suspicious classifier, utilizes 1115 core genes and is an ensemble classifier incorporating 12 individual models.ConclusionsThe accurate algorithmic depiction of this complex biological system among Hürthle subtypes results in a dramatic improvement of classification performance; specificity among Hürthle cell neoplasms increases from 11.8% with the GEC to 58.8% with the GSC, while maintaining the same sensitivity of 89%

Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BackgroundIdentification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by histopathological examination of tissue following surgical resection. Reliance on histopathological evaluation requires patients to undergo surgery to obtain a diagnosis despite most being non-cancerous. It is highly desirable to avoid surgery and to provide accurate classification of benignity versus malignancy from FNAB preoperatively. In our first-generation algorithm, Gene Expression Classifier (GEC), we achieved this goal by using machine learning (ML) on gene expression features. The classifier is sensitive, but not specific due in part to the presence of non-neoplastic benign Hürthle cells in many FNAB.ResultsWe sought to overcome this low-specificity limitation by expanding the feature set for ML using next-generation whole transcriptome RNA sequencing and called the improved algorithm the Genomic Sequencing Classifier (GSC). The Hürthle identification leverages mitochondrial expression and we developed novel feature extraction mechanisms to measure chromosomal and genomic level loss-of-heterozygosity (LOH) for the algorithm. Additionally, we developed a multi-layered system of cascading classifiers to sequentially triage Hürthle cell-containing FNAB, including: 1. presence of Hürthle cells, 2. presence of neoplastic Hürthle cells, and 3. presence of benign Hürthle cells. The final Hürthle cell Index utilizes 1048 nuclear and mitochondrial genes; and Hürthle cell Neoplasm Index leverages LOH features as well as 2041 genes. Both indices are Support Vector Machine (SVM) based. The third classifier, the GSC Benign/Suspicious classifier, utilizes 1115 core genes and is an ensemble classifier incorporating 12 individual models.ConclusionsThe accurate algorithmic depiction of this complex biological system among Hürthle subtypes results in a dramatic improvement of classification performance; specificity among Hürthle cell neoplasms increases from 11.8% with the GEC to 58.8% with the GSC, while maintaining the same sensitivity of 89%

AHNS Series: Do you know your guidelines? AHNS Endocrine Section Consensus Statement: State-of-the-art thyroid surgical recommendations in the era of noninvasive follicular thyroid neoplasm with papillary-like nuclear features.

The newly introduced pathologic diagnosis of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) will result in less bilateral thyroid surgery as well as deescalation in T4 suppressive and radioactive iodine treatment. Although, NIFTP is a nonmalignant lesion that has nuclear features of some papillary malignancies, the challenge for the surgeon is to identify a lesion as possibly NIFTP before the pathologic diagnosis. NIFTP, due to its reduction of overall rates of malignancy, will result in the initial surgical pendulum swinging toward lobectomy instead of initial total thyroidectomy. This American Head and Neck Society endocrine section consensus statement is intended to inform preoperative evaluation to attempt to identify those patients whose final pathology report may ultimately harbor NIFTP and can be offered a conservative surgical plan to assist in cost-effective, optimal management of patients with NIFTP

Preoperative Identification of Medullary Thyroid Carcinoma (MTC): Clinical Validation of the Afirma MTC RNA-Sequencing Classifier.

Background: Cytopathological evaluation of thyroid fine-needle aspiration biopsy (FNAB) specimens can fail to raise preoperative suspicion of medullary thyroid carcinoma (MTC). The Afirma RNA-sequencing MTC classifier identifies MTC among FNA samples that are cytologically indeterminate, suspicious, or malignant (Bethesda categories III-VI). In this study we report the development and clinical performance of this MTC classifier. Methods: Algorithm training was performed with a set of 483 FNAB specimens (21 MTC and 462 non-MTC). A support vector machine classifier was developed using 108 differentially expressed genes, which includes the 5 genes in the prior Afirma microarray-based MTC cassette. Results: The final MTC classifier was blindly tested on 211 preoperative FNAB specimens with subsequent surgical pathology, including 21 MTC and 190 non-MTC specimens from benign and malignant thyroid nodules independent from those used in training. The classifier had 100% sensitivity (21/21 MTC FNAB specimens correctly called positive; 95% confidence interval [CI] = 83.9-100%) and 100% specificity (190/190 non-MTC FNAs correctly called negative; CI = 98.1-100%). All positive samples had pathological confirmation of MTC, while all negative samples were negative for MTC on surgical pathology. Conclusions: The RNA-sequencing MTC classifier accurately identified MTC from preoperative thyroid nodule FNAB specimens in an independent validation cohort. This identification may facilitate an MTC-specific preoperative evaluation and resulting treatment

Performance of a Genomic Sequencing Classifier for the Preoperative Diagnosis of Cytologically Indeterminate Thyroid Nodules.

ImportanceUse of next-generation sequencing of RNA and machine learning algorithms can classify the risk of malignancy in cytologically indeterminate thyroid nodules to limit unnecessary diagnostic surgery.ObjectiveTo measure the performance of a genomic sequencing classifier for cytologically indeterminate thyroid nodules.Design, setting, and participantsA blinded validation study was conducted on a set of cytologically indeterminate thyroid nodules collected by fine-needle aspiration biopsy between June 2009 and December 2010 from 49 academic and community centers in the United States. All patients underwent surgery without genomic information and were assigned a histopathology diagnosis by an expert panel blinded to all genomic information. There were 210 potentially eligible thyroid biopsy samples with Bethesda III or IV indeterminate cytopathology that constituted a cohort previously used to validate the gene expression classifier. Of these, 191 samples (91.0%) had adequate residual RNA for validation of the genomic sequencing classifier. Algorithm development and independent validation occurred between August 2016 and May 2017.ExposuresThyroid nodule surgical histopathology diagnosis by an expert panel blinded to all genomic data.Main outcomes and measuresThe primary end point was measurement of genomic sequencing classifier sensitivity, specificity, and negative and positive predictive values in biopsies from Bethesda III and IV nodules. The secondary end point was measurement of classifier performance in biopsies from Bethesda II, V, and VI nodules.ResultsOf the 183 included patients, 142 (77.6%) were women, and the mean (range) age was 51.7 (22.0-85.0) years. The genomic sequencing classifier had a sensitivity of 91% (95% CI, 79-98) and a specificity of 68% (95% CI, 60-76). At 24% cancer prevalence, the negative predictive value was 96% (95% CI, 90-99) and the positive predictive value was 47% (95% CI, 36-58).Conclusions and relevanceThe genomic sequencing classifier demonstrates high sensitivity and accuracy for identifying benign nodules. Its 36% increase in specificity compared with the gene expression classifier potentially increases the number of patients with benign nodules who can safely avoid unnecessary diagnostic surgery