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.     

Effect of iron deficiency without anaemia on days alive and out of hospital in patients undergoing valvular heart surgery

Comprehensive evidence regarding the treatment of non-anaemic iron deficiency in patients undergoing valvular heart surgery is lacking. This study aimed to investigate the association between non-anaemic iron deficiency and postoperative outcomes in these patients. We retrospectively analysed 321 patients of which 180 (56%) had iron deficiency (defined as serum ferritin < 100 ng.ml^-1 or < 300 ng.ml^-1 with transferrin saturation < 20%). While the iron-deficient group had lower pre-operative haemoglobin levels than the non-iron deficient group (median (IQR [range]) 134 (127–141 [120–172]) g.l^-1, 143 (133–150 [120–179]) g.l^-1, p = 0.001), there was no between-group difference in allogeneic red blood cell transfusion. Median (IQR [range]) days alive and out of hospital at postoperative day 90 was 1 day shorter in the iron-deficient group (80 (77–82 [9–85]) days vs. 81 (79–83 [0–85]) days, p = 0.026). In multivariable analysis, only cardiopulmonary bypass duration (p = 0.032) and intra-operative allogeneic red blood cell transfusion (p = 0.011) were significantly associated with reduced days alive and out of hospital at postoperative day 90. Iron deficiency did not exert any adverse influence on secondary outcomes except length of hospital stay. Our findings indicate that non-anaemic iron deficiency alone is not associated with adverse effects in patients undergoing valvular heart surgery when it does not translate into an increased risk of allogeneic transfusion.     

The success of Australia’s ‘No Jab,No Pay’ policy at a local level; retrospective clinical audit of a single medical practice assessing incidence of catch-up vaccinations

Vaccination is a vital health care initiative to prevent individual and population infection. To increase vaccination rates the federal government implemented the ‘No Jab, No Pay’ policy, where eligibility for several government benefits required children to be fully vaccinated by removing ‘conscientious objections’ and expanding the age range of children whose families receive benefits. This study assesses the impact of this policy at a local area within a single medical practice community in NSW, Australia. A retrospective clinical audit was performed between 2012 and 2017 on a single general practice's vaccination records for children ≤19 years. Catch-up vaccinations were assessed based on age at vaccination. Incidence of catch-up vaccinations was assessed for each of four years before and two years after the implementation of the ‘No Jab, No Pay’ policy in January 2016, along with the age of children and vaccination(s) given. Catch-up vaccinations were assessed temporally either side of implementation of ‘No Jab, No Pay’. Comparing the average annual vaccination catch-up incidence rate of 6.2% pre-implementation (2012–2015), there was an increase to 9.2% in 2016 (p < .001) and 7.8% in 2017 (p = .027). Secondary outcome measurement of catch-up vaccination incidence rates before (2012–2015) and after (2016–2017) ‘No Jab, No Pay’ implementation showed statistically significant increases for children aged 8–11 years (3.2%–5.6%, p = .038), 12–15 years (7.5%–14.7%, p < .001) and 16–19 years (3.3%–10.2%, p < .001) along with a statistically significant reduction in children aged 1–3 years (11.4%–6.2%, p = .015). Also, catch-up rates for DTPa significantly increased after program implementation. This study demonstrates that the Australian federal government vaccination policy ‘No Jab, No Pay’ was coincident with an increase in catch-up vaccinations within a rural NSW community served by one medical practice, especially for older children.