PREDICT-GTN 2: Two-factor streamlined models match FIGO performance in gestational trophoblastic neoplasia.

OBJECTIVE: The International Federation of Gynecology and Obstetrics (FIGO) scoring system uses the sum of eight risk-factors to predict single-agent chemotherapy resistance in Gestational Trophoblastic Neoplasia (GTN). To improve ease of use, this study aimed to generate: (i) streamlined models that match FIGO performance and; (ii) visual-decision aids (nomograms) for guiding management. METHODS: Using training (n = 4191) and validation datasets (n = 144) of GTN patients from two UK specialist centres, logistic regression analysis generated two-factor models for cross-validation and exploration. Performance was assessed using true and false positive rate, positive and negative predictive values, Bland-Altman calibration plots, receiver operating characteristic (ROC) curves, decision-curve analysis (DCA) and contingency tables. Nomograms were developed from estimated model parameters and performance cross-checked upon the training and validation dataset. RESULTS: Three streamlined, two-factor models were selected for analysis: (i) M1, pre-treatment hCG + history of failed chemotherapy; (ii) M2, pre-treatment hCG + site of metastases and; (iii) M3, pre-treatment hCG + number of metastases. Using both training and validation datasets, these models showed no evidence of significant discordance from FIGO (McNemar's test p > 0.78) or across a range of performance parameters. This behaviour was maintained when applying algorithms simulating the logic of the nomograms. CONCLUSIONS: Our streamlined models could be used to assess GTN patients and replace FIGO, statistically matching performance. Given the importance of imaging parameters in guiding treatment, M2 and M3 are favoured for ongoing validation. In resource-poor countries, where access to specialist centres is problematic, M1 could be pragmatically implemented. Further prospective validation on a larger cohort is recommended.

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.

Computed tomography chest imaging offers no advantage over chest X-ray in the initial assessment of gestational trophoblastic neoplasia.

BACKGROUND: The International Federation of Gynaecology and Obstetrics (FIGO) score identifies gestational trophoblastic neoplasia (GTN) patients as low- or high-risk of single-agent chemotherapy resistance (SACR). Computed tomography (CT) has greater sensitivity than chest X-ray (CXR) in detecting pulmonary metastases, but effects upon outcomes remain unclear. METHODS: Five hundred and eighty-nine patients underwent both CXR and CT during GTN assessment. Treatment decisions were CXR based. The number of metastases, risk scores, and risk category using CXR versus CT were compared. CT-derived chest assessment was evaluated as impact upon treatment decision compared to patient outcome, incidence of SACR, time-to-normal human chorionic gonadotrophin hormone (TNhCG), and primary chemotherapy resistance (PCR). RESULTS: Metastasis detection (p < 0.0001) and FIGO score (p = 0.001) were higher using CT versus CXR. CT would have increased FIGO score in 188 (31.9%), with 43 re-classified from low- to high-risk, of whom 23 (53.5%) received curative single-agent chemotherapy. SACR was higher when score (p = 0.044) or risk group (p < 0.0001) changed. Metastases on CXR (p = 0.019) but not CT (p = 0.088) lengthened TNhCG. Logistic regression analysis found no difference between CXR (area under the curve (AUC) = 0.63) versus CT (AUC = 0.64) in predicting PCR. CONCLUSIONS: CT chest would improve the prediction of SACR, but does not influence overall treatment outcome, TNhCG, or prediction of PCR. Lower radiation doses and cost mean ongoing CXR-based assessment is recommended.

Salivary Cortisone to Estimate Cortisol Exposure and Sampling Frequency Required Based on Serum Cortisol Measurements.

Context: Population studies frequently measure cortisol as a marker of stress, and excess cortisol is associated with increased mortality. Cortisol has a circadian rhythm, and frequent blood sampling is impractical to assess cortisol exposure. We investigated measuring salivary cortisone and examined the sampling frequency required to determine cortisol exposure. Methods: Serum and saliva with cortisol and cortisone were measured by liquid chromatography-tandem mass spectrometry in independent cohorts. The relationship between serum cortisol and salivary cortisone was analyzed in cohort 1 using a linear mixed effects model. The resulting fixed effects component was applied to cohort 2. Saliva cannot easily be collected when a patient is sleeping, so we determined the minimum sampling required to estimate cortisol exposure [estimated area under the curve (eAUC)] using 24-hour cortisol profiles (AUC24) and calculated the relative error (RE) for eAUC. Results: More than 90% of variability in salivary cortisone could be accounted for by change in serum cortisol. A single serum cortisol measurement was a poor estimate of AUC24, especially in the morning or last thing at night (RE >68%); however, three equally spaced samples gave a median RE of 0% (interquartile range, -15.6% to 15.1%). In patients with adrenal incidentalomas, eAUC based on three serum cortisol samples showed a difference between those with autonomous cortisol secretion and those without (P = 0.03). Interpretation: Accepting that most people sleep 7 to 8 hours, ∼8-hourly salivary cortisone measurements provide a noninvasive method of estimating 24-hour cortisol exposure for population studies.

Resetting the Abnormal Circadian Cortisol Rhythm in Adrenal Incidentaloma Patients With Mild Autonomous Cortisol Secretion.

Context: Adrenal incidentalomas (AIs) are found commonly on axial imaging. Around 30% exhibit autonomous cortisol secretion (ACS) associated with increased cardiovascular events and death. Objective: We hypothesized that AI/ACS patients have an abnormal cortisol rhythm that could be reversed by use of carefully timed short-acting cortisol synthesis blockade, with improvement in cardiovascular disease markers. Design, Setting, and Participants: In a phase 1/2a, prospective study (Eudract no. 2012-002586-35), we recruited six patients with AI/ACS and two control groups of six sex-, age-, and body mass index-matched individuals: (1) patients with AI and no ACS (AI/NoACS) and (2) healthy volunteers with no AI [healthy controls (HC)]. Twenty-four-hour circadian cortisol analysis was performed to determine any differences between groups and timing of intervention for cortisol lowering using the 11ß-hydroxylase inhibitor metyrapone. Circadian profiles of serum interleukin-6 (IL-6) were assessed. Results: Serum cortisol levels in group AI/ACS were significantly higher than both group AI/NoACS and group HC from 6 pm to 10 pm [area under the curve (AUC) difference: 0.81 nmol/L/h; P = 0.01] and from 10 pm to 2 am (AUC difference: 0.86 nmol/L/h; P < 0.001). In light of these findings, patients with ACS received metyrapone 500 mg at 6 pm and 250 mg at 10 pm, and cortisol rhythms were reassessed. Postintervention evening serum cortisol was lowered, similar to controls [6 pm to 10 pm (AUC difference: -0.06 nmol/L/h; P = 0.85); 10 pm to 2 am (AUC difference: 0.10 nmol/L/h; P = 0.76)]. Salivary cortisone showed analogous changes. IL-6 levels were elevated before treatment [10 pm to 2 pm (AUC difference: 0.42 pg/mL/h; P = 0.01)] and normalized post treatment. Conclusions: In AI/ACS, the evening and nocturnal cortisol exposure is increased. Use of timed evening doses of metyrapone resets the cortisol rhythm to normal. This unique treatment paradigm is associated with a reduction in the cardiovascular risk marker IL-6.

Hormonal circadian rhythms in patients with congenital adrenal hyperplasia: identifying optimal monitoring times and novel disease biomarkers.

OBJECTIVES: The treatment goal in congenital adrenal hyperplasia (CAH) is to replace glucocorticoids while avoiding androgen excess and iatrogenic Cushing's syndrome. However, there is no consensus on how to monitor disease control. Our main objectives were to evaluate hormonal circadian rhythms and use these profiles to identify optimal monitoring times and novel disease biomarkers in CAH adults on intermediate- and long-acting glucocorticoids. DESIGN: This was an observational, cross-sectional study at the National Institutes of Health Clinical Center in 16 patients with classic CAH. METHODS: Twenty-four-hour serum sampling for ACTH, 17-hydroxyprogesterone (17OHP), androstenedione (A4), androsterone, DHEA, testosterone, progesterone and 24-h urinary pdiol and 5ß-pdiol was carried out. Bayesian spectral analysis and cosinor analysis were performed to detect circadian rhythmicity. The number of hours to minimal (TminAC) and maximal (TmaxAC) adrenocortical hormone levels after dose administration was calculated. RESULTS: A significant rhythm was confirmed for ACTH (r(2), 0.95; P<0.001), 17OHP (r(2), 0.70; P=0.003), androstenedione (r(2), 0.47; P=0.043), androsterone (r(2), 0.80; P<0.001), testosterone (r(2), 0.47; P=0.042) and progesterone (r(2), 0.64; P=0.006). The mean (s.d.) TminAC and TmaxAC for 17OHP and A4 were: morning prednisone (4.3 (2.3) and 9.7 (3.5) h), evening prednisone (4.5 (2.0) and 10.3 (2.4) h), and daily dexamethasone (9.2 (3.5) and 16.4 (7.2) h). AUC0-24 h progesterone, androsterone and 24-h urine pdiol were significantly related to 17OHP. CONCLUSION: In CAH patients, adrenal androgens exhibit circadian rhythms influenced by glucocorticoid replacement. Measurement of adrenocortical hormones and interpretation of results should take into account the type of glucocorticoid and time of dose administration. Progesterone and backdoor metabolites may provide alternative disease biomarkers.

Much of the variation in breast pathology quality assurance data in the UK can be explained by the random order in which cases arrive at individual centres, but some true outliers do exist.

AIMS: To investigate the role of random temporal order of patient arrival at screening centres in the variability seen in rates of node positivity and breast cancer grade between centres in the NHS Breast Screening Programme. METHODS AND RESULTS: Computer simulations were performed of the variation in node positivity and breast cancer grade with the random temporal arrival of patients at screening centres based on national UK audit data. Cumulative mean graphs of these data were plotted. Confidence intervals for the parameters were generated, using the binomial distribution. UK audit data were plotted on these control limit graphs. The results showed that much of the variability in the audit data could be accounted for by the effects of random order of arrival of cases at the screening centres. Confidence intervals of 99.7% identified true outliers in the data. CONCLUSIONS: Much of the variation in breast pathology quality assurance data in the UK can be explained by the random order in which cases arrive at individual centres. Control charts with confidence intervals of 99.7% plotted against the number of reported cases are useful tools for identification of true outliers.

Laboratory assessment of iron status in pregnancy.

BACKGROUND: Efforts to improve maternal nutrition during pregnancy prompted an observational study of the occurrence of maternal iron deficiency and its laboratory diagnosis in almost 500 pregnancies. METHODS: In this longitudinal study, the biochemical and haematological iron indices of women (n=492) attending a prenatal clinic in a Dublin maternity hospital were assessed at first booking (mean 15.9 weeks), and after 24 weeks, and 36 weeks of gestation. Full blood counts were measured. Serum ferritin (SF), zinc protoporphyrin (ZPP), and transferrin receptor (sTfR) concentrations were assayed and transferrin receptor index (sTfR-Index) was calculated. The occurrence of low values and their diagnostic values were considered. RESULTS: A high occurrence iron deficiency (ID) at first booking (SF<12 µg/L) had increased over six-fold by 24 weeks, and all biochemical iron indices reflected progressive iron depletion right up to term. The WHO recommended anaemia "cut-off" (Hb<110 g/L) was insensitive to biochemical iron deficiency at booking, missing over 90% of the low SF values (SF<12 µg/L) which were mostly associated with much higher Hb levels. CONCLUSIONS: This study stresses the importance of including a biochemical index of iron status in prenatal screening and supports SF as the best indicator of biochemical ID overall. sTfR was insensitive to iron deficiency in early pregnancy, whereas the sTfR-Index, as a ratio, has the potential to distinguish between ID and physiological anaemia, and may offer stability in the assessment of iron stores from early pregnancy to full term. A policy of early screening of both Hb and SF concentrations is recommended as the minimum requirement for surveillance of maternal iron status in pregnancy.