Objective To conduct a cost minimisation analysis of three methods of gestational diabetes mellitus (GDM) screening and diagnosis.Design Prospective randomised controlled trial.Setting University teaching hospital.Population Pregnant women (n = 1594) presenting for GDM screening.Methods Women presenting for GDM screening, who consented to participate, were randomised to GR1 [1-hour, 50-g glucose screen (GS) ± 3-hour, 100-g oral glucose tolerance test (OGTT)], GR2 (50-g GS ± 2-hour, 75-g OGTT) or GR3 (2-hour, 75-g OGTT). Demographics, health and time/travel cost information were assessed for each glucose testing visit.Main outcome measures Costs (direct and indirect) and prevalence of GDM diagnosis.Results The direct sampling costs of the glucose tests per woman were as follows: GS, CAN$12.57; 75-g OGTT, $36.10; 100-g OGTT, CAN$48.13. Among women in the two-step method groups diagnosed with GDM, 39% of the GR1 and 61% of the GR2 groups were diagnosed at the first step by GS ‡ 10.3 mmol/l, according to the Canadian Diabetes Association recommendations, contributing to a lower total cost in these groups. The total costs per woman screened were as follows: GR1, CAN$91.61; GR2, CAN$89.03; GR3, CAN$108.38. The GDM prevalence was similar (3.7%, 3.7% and 3.6%, respectively). The higher costs of GR3 were related to more blood draws and the time required for all women to undergo the 2-hour OGTT.Conclusions Careful consideration should be given to an internationally recommended method of universal screening for GDM which minimises the burden and cost for individual women and the healthcare system, yet provides diagnostic efficacy. The two-step method (GS ± OGTT) accomplished this better than the one-step method (75-g OGTT).Keywords Cost analysis, diagnosis, direct/indirect costs, gestational diabetes mellitus, oral glucose tolerance test, screening.Please cite this paper as: Meltzer S, Snyder J, Penrod J, Nudi M, Morin L. Gestational diabetes mellitus screening and diagnosis: a prospective randomised controlled trial comparing costs of one-step and two-step methods. BJOG 2010;117:407-415.

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Background: High PD-L1 expression (50%) is a routine biomarker but is incompletely predictive, with response rates to PD-1 monotherapy only 35-45% in patients with lung cancer. Beyond PD-L1, additional individual pre-treatment variables, including clinical (smoking history, BMI), genomic (TMB, STK11, EGFR), and laboratory features (baseline dNLR), individually associate with response but have not been comprehensively examined in combination. We hypothesized that a multifactorial model incorporating routinely available clinical, pathologic, and genomic variables could improve prediction of response in high PD-L1 patients receiving first line anti-PD-(L)1 monotherapy. Method: 190 patients from MSKCC with advanced, PD-L1 high NSCLC (PD-L1 50%) treated with PD-1 or PD-L1 inhibitor were identified and separated into training (n¼134, 70%) and validation cohorts (n¼56, 30%). In addition to PD-L1 expression, 39 variables were collected, including histology, clinical (age, gender, performance status, smoking, clinical trial vs standard of care treatment), molecular (TMB, EGFR, KRAS, STK11, KEAP1, TP53, ALK, ROS1, BRAF), and baseline CBC (including dNLR). Radiologic response assessments were performed according to RECIST 1.1. To distinguish responders vs. non-responders, a logistic regression classifier with an elastic net penalty was used to restrict the number of variables considered and to optimize generalizability to independent cohorts. The parameters of the model were optimized using only the training cohort and its performance was measured on the validation cohort. Result: In PD-L1 high NSCLC patients treated with PD-(L)1 blockade, the ORR was 43%. In the training cohort, 5 features (PD-L1 expression, current smoking status, lymphocyte count, platelets, total WBC) associated with response. Three features (EGFR mutation, STK11 mutation, standard of care treatment) associated with lack of response. TMB was not predictive within this selected PD-L1 high cohort. In the training cohort, the eight identified features were used to develop a multifactorial model which improved BOR prediction (AUC 0.83) compared to PD-L1 alone (AUC 0.65), p¼0.02. Improved performance of the model was confirmed in the validation cohort (AUC 0.66 for multifactorial model vs. AUC 0.52 for PD-L1 alone). Conclusion: Among patients with high PD-L1 expression, multiple clinical, molecular, and baseline laboratory features impact response to PD-(L)1 monotherapy. The addition of these routinely available variables to PD-L1 in a multifactorial model improves prediction of response to PD-(L)1 blockade in patients with high PD-L1. This approach may help further stratify patients within the PD-L1 high population and identify which patients are likely to benefit from PD-(L)1 monotherapy vs those who should consider chemotherapy + immunotherapy.

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Objectives: To evaluate treatment sequences and associated costs among patients with relapsed/refractory multiple myeloma (RRMM). MethOds: Patients with RRMM between January 2007 and September 2013 were identified from US MarketScan databases. Outcomes included treatment regimen per line (L; 2-4L), sequences of treatment regimens, and cost per line and of progression (2L vs > 2L). All-cause and MM-specific monthly costs captured inpatient, outpatient, emergency department, and drug-related costs, adjusted for censoring. Results: 4449 MM patients initiated a 2L regimen, of whom 38% (n= 1696) progressed to 3L and 15% (n= 689) progressed to 4L. Median follow-up was 14 months (range 1-83). The most frequent 2L regimens were lenalidomide (18%), lenalidomide-dexamethasone (12%), bortezomib-dexamethasone (12%), bortezomib-lenalidomide-dexamethasone (10%), and bortezomib (7%). Of patients whose prior therapy included an immunomodulatory drug (IMiD) (n= 1752), bortezomib-dexamethasone was the most common 2L regimen (17%); for those with no prior IMiD exposure (n= 2697), lenalidomide was the most common 2L (23%). Median time to start of 3L was 5.8 months. Among the 27% of lenalidomide 2L patients who progressed to 3L, 64% had bortezomib-based regimens in 3L. Among the 47% of bortezomib-dexamethasone 2L patients who progressed to 3L, 63% had lenalidomide-based regimens in 3L. MM-specific costs were highest for all patients during the first year of 2L: $122,960 versus $74,573 (12-24 mths), $68,940 (24-36 mths), $59,327 (36+ mths). Drug-related costs accounted for 39-62%, and were dependent on regimen and treatment line. During 0-36 mths, MM-specific costs after progression from 2L were higher by $122,823 compared with costs incurred on 2L. cOnclusiOns: In this study of RRMM patients, 38% progressed to subsequent treatment lines, with variability in 2L regimens and treatment sequences. Highest costs were incurred during the first 12 months of follow-up. The cost of managing progressive disease in RRMM is high, as observed by the difference in costs before and after progression. PCN119 TreaTmeNT STraTegieS, healTh Care reSourCe uSe aNd CoSTS of aggreSSive hiSTologiCal TyPeS of NoN-hodgkiN lymPhomaS iN The Slovak rePubliC. reSulTS from The CroSS-SeCTioNal Survey iN The haemaTology-oNCologiCal CeNTerS