Adequacy Assessment in Lymph Node Aspirates: An Exploratory Cytomorphologic Analysis of Negative Cervical Node Aspirates of Head and Neck Carcinomas.
Fine-needle aspiration cytology (FNAC) of lymph node is sensitive for detection of metastatic carcinoma but not without a significant false-negative rate. This study reviews clinicocytological features of negative node aspirates to identify predictive factors for establishing adequacy criteria.
Negative FNAC specimens matched with neck dissection from a primary diagnosis of head and neck squamous cell, or undifferentiated (nasopharyngeal) carcinoma were reviewed for clinical and cytological parameters including lymphoid, inflammatory, and background components.
Slides from 86 lymph node aspirates including 50 positive for metastasis on follow-up were retrieved. Higher total lymphocyte count, lymphoid fragment count, germinal center fragment count, undifferentiated histology, presence of histiocytes and absence of blood were associated with a true negative cytologic diagnosis (p < 0.05), but not node size or location (p > 0.05). Undifferentiated histology, small lymphoid and germinal center fragments were independent factors indicative of a true negative diagnosis (p < 0.05). Large lymphoid fragments (p = 0.052) demonstrated a trend. Assessment of lymphoid components over five hotspots high-power fields (HPFs) was more robust in predictive value than only one hotspot. Receiver operating characteristic curve identified >10 small lymphoid, >20 large lymphoid and >2 germinal center fragment per five HPFs as optimal adequacy thresholds. Stricter total lymphocyte count cutoff accompanies increase of diagnostic accuracy, up to 0.67 for ≥5 HPFs with >500 lymphocytes.
Total counts of lymphoid and germinal center fragments from multiple HPFs are useful in adequacy assessment of lymph node aspirates and improve diagnostic performance of FNAC in exclusion of metastatic carcinoma.
Li J
，Ng JKM
，Tsang JY
，Tse GM
... -
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Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
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Sensitivity and Predictive Value of the Frozen Section of Sentinel Lymph Node Biopsy in the Post-neoadjuvant Setting: Experience From a Tertiary Care Hospital in a Resource-Limited Country.
Background Axillary lymph node status is one of the most important prognostic factors in breast cancer treatment, which can be confirmed by sentinel lymph node biopsy (SLNB). Intraoperative frozen section is an alternative method for SLNB, which can reduce the risks associated with secondary surgery. The feasibility and accuracy of SLNB after post-neoadjuvant chemotherapy (NACT) are affected by many factors as lymphatic drainage from the breast could be impaired due to fibrosis, fat necrosis, and granulation tissue formation, thus hampering the detection of the sentinel lymph node and afterward interpretation by pathologists due to therapy-related changes. Despite the increasing use of SLNB in post-NACT settings, there is still limited information on the accuracy of SLNB in resource-limited countries. Objective Our study aims to detect the sensitivity and predictive value of frozen section SLNB in the post-NACT setting while comparing it with final permanent histopathological results and considering final permanent histopathological results as standard. Materials and methods A total of 286 patients meeting the inclusion criteria from 2021 to 2022 were included in the study. Hematoxylin and eosin (H&E)-stained microscopic glass slides of frozen SLNB after NACT, permanent paraffin-embedded sections, and immunohistochemical stains were retrieved and reviewed. For all the categorical variables, including histologic type and grade, frequencies and percentages were obtained. Measures of central tendency and variability for continuous data such as age, number of sentinel lymph nodes received, and size of the largest nodal deposit were calculated. The chi-square test was used for the comparison of qualitative variables. A p-value of less than or equal to 0.05 was considered statistically significant. Results The median age of presentation was 47 years (range = 39 to 55 years). The median number of sentinel lymph nodes received was three (range = 2-4). At the time of frozen section reporting, out of a total of 286 cases, 229 (80.1%) cases were labeled as negative, 55 (19.2%) cases as positive, and two (0.7%) cases were deferred for permanent section results. Out of 229 cases labeled as negative at the time of the frozen section, 220 (76.9%) cases were true negative confirmed on permanent sections. A total of 66 (33.1%) cases were true positive, including two deferred cases and nine false negative cases, in addition to 55 cases labeled as positive on the initial frozen section. The study showed sensitivity, specificity, and accuracy of frozen section analysis of SLNB at 83.00%, 100%, and 96.15%, respectively, with a false negative rate (FNR) rate of 16.7%. Conclusion Further follow-up studies to definitively determine the role of SLNB following post-NACT in patients who did not undergo axillary lymph node dissection (ALND) are needed. Continuous monitoring of the rate of false positives and false negatives of frozen sections on SLNB is essential as feedback for pathologists.
Safdar F
，Vohra L
，Idress R
《Cureus》
ResearchGate
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钛学术
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