PALLIATION AND LIFE QUALITY IN LUNG-CANCER - HOW GOOD ARE CLINICIAN AT JUDGING TREATMENT OUTCOME

A recent trial by the MRC Lung Cancer Working Party used physician assessments to compare two palliative schedules of radiotherapy in lung cancer. A prospective study has been undertaken on a subset of these trial patients to see how physician assessments of symptomatic relief and general condition correlate with patient perception of therapeutic response. In 40 patients followed up monthly from presentation until close to death, good agreement was found between doctors and patients on change in specific physical symptoms and overall physical condition. Doctors were poor judges of life quality at presentation but appeared able to identify relative improvement or deterioration in overall quality of life. In conclusion, physician assessments may constitute valid end-points for radiotherapy trials comparing palliative schedules in lung cance

Ipsilateral breast tumour relapse: local recurrence versus new primary and the effect of whole breast radiotherapy on the rate of new primaries

PurposeThe justification for partial breast radiotherapy after breast conservation surgery assumes that ipsilateral breast tumor relapses (IBTR) outside the index quadrant are mostly new primary (NP) tumors that develop despite radiotherapy. We tested the hypothesis that whole-breast radiotherapy (WBRT) is ineffective in preventing NP by comparing development rates in irradiated and contralateral breasts after tumor excision and WBRT.Methods and MaterialsWe retrospectively reviewed 1,410 women with breast cancer who were entered into a prospective randomized trial of radiotherapy fractionation and monitored annually for ipsilateral breast tumor relapses (IBTR) and contralateral breast cancer (CLBC). Cases of IBTR were classified into local recurrence (LR) or NP tumors based on location and histology and were subdivided as definite or likely depending on clinical data. Rates of ipsilateral NP and CLBC were compared over a 15-year period of follow-up.ResultsAt a median follow-up of 10.1 years, there were 150 documented cases of IBTR: 118 (79%) cases were definite or likely LR; 27 (18%) cases were definite or likely NP; and 5 (3%) cases could not be classified. There were 71 cases of CLBC. The crude proportion of definite-plus-likely NP was 1.9% (27/1,410) patients compared with 5% (71/1,410) CLBC patients. Cumulative incidence rates at 5, 10, and 15 years were 0.8%, 2.0%, and 3.5%, respectively, for definite-plus-likely NP and 2.4%, 5.8%, and 7.9%, respectively for CLBC, suggesting a difference in the rates of NP and CLBC.ConclusionsThis analysis suggests that WBRT reduces the rate of ipsilateral NP tumors. The late presentation of NP has implications for the reporting of trials that are testing partial breast radiotherapy

The UK HeartSpare study: randomised evaluation of voluntary deep-inspiratory breath-hold in women undergoing breast radiotherapy

Purpose: to determine whether voluntary deep-inspiratory breath-hold (v_DIBH) and deep-inspiratory breath-hold with the active breathing coordinator™ (ABC_DIBH) in patients undergoing left breast radiotherapy are comparable in terms of normal-tissue sparing, positional reproducibility and feasibility of delivery.Methods: following surgery for early breast cancer, patients underwent planning-CT scans in v_DIBH and ABC_DIBH. Patients were randomised to receive one technique for fractions 1–7 and the second technique for fractions 8–15 (40?Gy/15 fractions total). Daily electronic portal imaging (EPI) was performed and matched to digitally-reconstructed radiographs. Cone-beam CT (CBCT) images were acquired for 6/15 fractions and matched to planning-CT data. Population systematic (?) and random errors (?) were estimated. Heart, left-anterior-descending coronary artery, and lung doses were calculated. Patient comfort, radiographer satisfaction and scanning/treatment times were recorded. Within-patient comparisons between the two techniques used the paired t-test or Wilcoxon signed-rank test.Results: twenty-three patients were recruited. All completed treatment with both techniques. EPI-derived ? were ?1.8?mm (v_DIBH) and ?2.0?mm (ABC_DIBH) and ? ?2.5?mm (v_DIBH) and ?2.2?mm (ABC_DIBH) (all p non-significant). CBCT-derived ? were ?3.9?mm (v_DIBH) and ?4.9?mm (ABC_DIBH) and ? ??4.1?mm (v_DIBH) and ??3.8?mm (ABC_DIBH). There was no significant difference between techniques in terms of normal-tissue doses (all p non-significant). Patients and radiographers preferred v_DIBH (p?=?0.007, p?=?0.03, respectively). Scanning/treatment setup times were shorter for v_DIBH (p?=?0.02, p?=?0.04, respectively).Conclusions: v_DIBH and ABC_DIBH are comparable in terms of positional reproducibility and normal tissue sparing. v_DIBH is preferred by patients and radiographers, takes less time to deliver, and is cheaper than ABC_DIB

Do we need an urgent ultrasound clinic for patients with rheumatological conditions? A service evaluation

#400WORDS: KNOWLEDGE + ACTIO

Modeling time‐to‐event (survival) data using classification tree analysis

Rationale, aims, and objectivesTime to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow‐up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a “decision‐tree”–like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross‐generalizability.MethodUsing empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross‐generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves.ResultsThe Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time.ConclusionsClassification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA‐survival framework.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141923/1/jep12779.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141923/2/jep12779_am.pd

Minimizing imbalances on patient characteristics between treatment groups in randomized trials using classification tree analysis

Rationale, aims, and objectivesRandomization ensures that treatment groups do not differ systematically in their characteristics, thereby reducing threats to validity that may otherwise explain differences in outcomes. Large observed imbalances in patient characteristics may indicate that selection bias is being introduced into the treatment allocation process. We introduce classification tree analysis (CTA) as a novel algorithmic approach for identifying potential imbalances in characteristics and their interactions when provisionally assigning each new participant to one or the other treatment group. The participant is then permanently assigned to the treatment group that elicits either no or less imbalance than if assigned to the alternate group.MethodUsing data on participant characteristics from a clinical trial, we compare 3 different treatment allocation approaches: permuted block randomization (the original allocation method), minimization, and CTA. Treatment allocation performance is assessed by examining balance of all 17 patient characteristics between study groups for each of the allocation techniques.ResultsWhile all 3 treatment allocation techniques achieved excellent balance on main effect variables, Classification tree analysis further identified imbalances on interactions and in the distributions of some of the continuous variables.ConclusionsClassification tree analysis offers an algorithmic procedure that may be used with any randomization methodology to identify and then minimize linear, nonlinear, and interactive effects that induce covariate imbalance between groups. Investigators should consider using the CTA approach as a real‐time complement to randomization for any clinical trial to safeguard the treatment allocation process against bias.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141083/1/jep12792.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141083/2/jep12792_am.pd

Lemons and Other Grand Delusions

Lemons and Other Grand Delusions explores a host of characters as they come face to face with their greatest fears, as they get exactly what they think they want. From magic dimension-bending lemons, to automatons powered by the Philosopher’s Stone, as the powers from beyond become in-hand realities, the characters find their greatest desires are not as simple and powerful in their hands as they first thought. Exploring the limits of greed and desire within ourselves and in the society we live in, the collection asks who are we, if not a collection of our own desires, and the impulses to fight them