Impact of bariatric surgery on oral anticancer drugs: an analysis of real-world data

PURPOSE

The number of patients with bariatric surgery who receive oral anticancer drugs is rising. Bariatric surgery may affect the absorption of oral anticancer drugs. Strikingly, no specific drug dosing recommendations are available. We aim to provide practical recommendations on the application of oral anticancer drugs in patients who underwent bariatric surgery.

METHODS

Patients with any kind of bariatric surgery were extracted retrospectively in a comprehensive cancer center. In addition, a flowchart was proposed to assess the risk of inadequate exposure to oral anticancer drugs in patients who underwent bariatric surgery. Subsequently, the flowchart was evaluated retrospectively using routine Therapeutic drug monitoring (TDM) samples.

RESULTS

In our analysis, 571 cancer patients (0.4% of 140.000 treated or referred patients) had previous bariatric surgery. Of these patients, 78 unique patients received 152 oral anticancer drugs equaling an overall number of 30 unique drugs. The 30 different prescribed oral anticancer drugs were categorized as low risk (13%), medium risk (67%), and high risk (20%) of underdosing. TDM plasma samples of 25 patients (82 samples) were available, of which 21 samples post-bariatric surgery (25%) were below the target value.

CONCLUSIONS

The proposed flowchart can support optimizing the treatment with orally administered anticancer drugs in patients who underwent bariatric surgery. We recommend performing TDM in drugs that belong to BCS classes II, III, or IV. If more risk factors are present in BCS classes II or IV, a priori switches to other drugs may be advised. In specific cases, higher dosages can be provided from the start (e.g., tamoxifen).

Cortisol as Biomarker for CYP17-Inhibition is Associated with Therapy Outcome of Abiraterone Acetate

BACKGROUND

Abiraterone acetate is an irreversible 17α-hydroxylase/C17, 20-lyase (CYP17) inhibitor approved for the treatment of metastatic castration-resistant prostate cancer (mCRPC) patients. Inhibition of this enzyme leads to low testosterone and cortisol levels in blood. There is growing evidence that clinical efficacy of abiraterone is related to the rate of suppression of serum testosterone. However, quantification of very low levels of circulating testosterone is challenging. We therefore aimed to investigate whether circulating cortisol levels could be used as a surrogate biomarker for CYP17 inhibition in patients with mCRPC treated with abiraterone acetate.

PATIENTS AND METHODS

mCRPC patients treated with abiraterone acetate were included. Abiraterone and cortisol levels were measured with a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS). On treatment cortisol and abiraterone concentrations were related to treatment response and progression free survival.

RESULTS

In total 117 patients were included with a median cortisol concentration of 1.13 ng/ml (range: 0.03 - 82.2) and median abiraterone trough concentration (Cmin) of 10.2 ng/ml (range: 0.58 - 92.1). In the survival analyses, abiraterone Cmin ≥ 8.4 ng/mL and cortisol  < 2.24 ng/mL were associated with a longer prostate-specific antigen (PSA) independent progression-free survival than patients with an abiraterone concentration  ≥ 8.4 ng/mL and a cortisol concentration ≥ 2.24 ng/mL (13.8 months vs. 3.7 months).

CONCLUSION

Our study shows that cortisol is not an independent predictor of abiraterone response in patients with mCRPC, but it is of added value in combination with abiraterone levels, to predict a response on abiraterone.

Pharmacokinetic boosting of olaparib: A randomised, cross-over study (PROACTIVE-study)

BACKGROUND

Pharmacokinetic (PK) boosting is the intentional use of a drug-drug interaction to enhance systemic drug exposure. PK boosting of olaparib, a CYP3A-substrate, has the potential to reduce PK variability and financial burden. The aim of this study was to investigate equivalence of a boosted, reduced dose of olaparib compared to the non-boosted standard dose.

METHODS

This cross-over, multicentre trial compared olaparib 300 mg twice daily (BID) with olaparib 100 mg BID boosted with the strong CYP3A-inhibitor cobicistat 150 mg BID. Patients were randomised to the standard therapy followed by the boosted therapy, or vice versa. After seven days of each therapy, dense PK sampling was performed for noncompartmental PK analysis. Equivalence was defined as a 90% Confidence Interval (CI) of the geometric mean ratio (GMR) of the boosted versus standard therapy area under the plasma concentration-time curve (AUC0-12 h) within no-effect boundaries. These boundaries were set at 0.57-1.25, based on previous pharmacokinetic studies with olaparib capsules and tablets.

RESULTS

Of 15 included patients, 12 were eligible for PK analysis. The GMR of the AUC0-12 h was 1.45 (90% CI 1.27-1.65). No grade ≥3 adverse events were reported during the study.

CONCLUSIONS

Boosting a 100 mg BID olaparib dose with cobicistat increases olaparib exposure 1.45-fold, compared to the standard dose of 300 mg BID. Equivalence of the boosted olaparib was thus not established. Boosting remains a promising strategy to reduce the olaparib dose as cobicistat increases olaparib exposure Adequate tolerability of the boosted therapy with higher exposure should be established.

External validity of an automated delirium prediction model (DEMO) and comparison to the manual VMS-questions: a retrospective cohort study

BACKGROUND

It is estimated that one-third of delirium cases in hospitals could be prevented with appropriate interventions. In Dutch hospitals a manual instrument (VMS-questions) is used to identify patients at-risk for delirium. Delirium Model (DEMO) is an automated model which could support delirium prevention more efficiently. However, it has not been validated beyond the hospital it was developed in.

AIM

To externally validate the DEMO and compare its performance to the VMS-questions.

METHOD

A retrospective cohort study between July and December 2018 was conducted. Delirium cases were identified through a chart review, and the VMS-questions were extracted from the electronic health records. The DEMO was validated in patients ≥ 60 years, and a comparison with the VMS-questions was made in patients ≥ 70 years.

RESULTS

In total 1,345 admissions were included. The DEMO predicted 59 out of 75 delirium cases (sensitivity 0.79, 95% CI = 0.68-0.87; specificity 0.75, 95% CI = 0.72-0.77). Compared to the VMS-questions, the DEMO showed a lower specificity (0.64 vs. 0.72; p < 0.001) and a comparable sensitivity (0.83 vs. 0.80; p = 0.56). The VMS-questions were missing in 20% of admissions, in which the DEMO correctly predicted 10 of 12 delirium cases.

CONCLUSION

The DEMO showed acceptable performance for delirium prediction. Overall the DEMO predicted more delirium cases because the VMS-questions were missing in 20% of admissions. This study shows that automated instruments such as DEMO could play a key role in the efficient and timely deployment of measures to prevent delirium.

Exposure-Response Analyses of Olaparib in Real-Life Patients with Ovarian Cancer

BACKGROUND

Olaparib is given in a fixed dose of twice-daily 300 mg in patients who are diagnosed with ovarian cancer, breast cancer, prostate cancer or pancreas cancer and has a high interpatient variability in pharmacokinetic exposure. The objective of this study was to investigate whether pharmacokinetic exposure of olaparib is related to efficacy and safety in a real-life patient' cohort.

METHODS

A longitudinal observational study was conducted in patients who received olaparib for metastatic ovarian cancer of whom pharmacokinetic samples were collected. A Kaplan-Meier analyses was used to explore the relationship between olaparib exposure, measured as (calculated) minimum plasma concentrations (C_min), and efficacy, Univariate and multivariate cox-regression analyses were performed. Also, the C_min of patients who experienced toxicity was compared with patients who did not experience any toxicity.

RESULTS

Thirty-five patients were included in the exposure-efficacy analyses, with a median olaparib C_min of 1514 ng/mL. There was no statistical significant difference in PFS of patients below and above the median C_min concentration of olaparib, with a hazard ratio of 1.06 (95% confidence interval: 0.46-2.45, p = 0.9)). For seven patients pharmacokinetic samples were available before toxicity occurred, these patients had a higher C_min of olaparib in comparison with patients who had not experienced any toxicity (n = 33), but it was not statistically significant (p = 0.069).

CONCLUSIONS

Our study shows that exposure of olaparib is not related to PFS. This suggests that the approved dose of olaparib yields sufficient target inhibition in the majority of patients.