Weight Loss at First Month and Development of Tolerance as Possible Predictors of 30 mg Phentermine Efficacy at 6 Months

The efficacy of anti-obesity drugs usually does not consider the high degree of interindividual variability in responses to the drug which could affect the decision to withdraw the drug early due to ineffectiveness or to continue therapy according to specific expectations of success. The aim of this study was to analyze body weight loss in kilograms during the first month (1 mo-BWLkg) of treatment with 30 mg phentermine and development of tolerance to phentermine, on its 6-month efficacy. One hundred sixty-six subjects with obesity were individually or jointly analyzed in the study. Subjects with 1 mo-BWLkg of <1 kg, 1–3 kg, 3–5 kg, and ≥5 kg reached 6-month mean percentage body weight reductions (BWR%) of approximately 3%, 5%, 10%, and 15%, respectively. Development of late tolerance (4–6 months) to phentermine had a lower impact than early tolerance (2–3 months). Subjects with 1 mo-BWLkg <3 kg who developed early tolerance did not achieve relevant BWR% (≥5%) at month 6, while the rest of the subgroups achieved increasing and progressive BWR%, according to their 1 mo-BWLkg range and time of onset of tolerance. The 1 mo-BWLkg and development of tolerance to phentermine could be useful to predict the expected 6-month efficacy trends in obese patients treated with 30 mg phentermine.

29. Impact of Antimicrobial Stewardship Intervention on Unrestricted Meropenem Use Upon Transitions of Care

Background Broad-spectrum antimicrobials, like carbapenems, are often initiated empirically and can be continued for long periods of time, which may increase rates of multi-drug resistant organisms. Antimicrobial stewardship programs (ASP) have been shown to decrease the duration of antimicrobial therapy. Since July 2017 at UTMB Health, meropenem use has been restricted to infectious diseases and intensive care unit (ICU) providers. This study evaluated the impact of an electronic medical record (EMR)-based ASP intervention on meropenem days of therapy (DOT) in patients transitioning from the ICU to the general floors. Methods Patients aged at least 18 years with an active medication order for meropenem upon transition from an ICU to a medical/surgical unit were included. Once transitioned, the active meropenem order appeared in the “review” column of the pharmacists’ queue. Pharmacists contacted the primary team, requested infectious diseases or ASP approval to continue therapy, and documented communication in the chart. Data for the pre- and post-intervention groups was collected retrospectively for the months of November 2017 to April 2018 and March 2020 to August 2020. The primary outcome of the study was meropenem DOT after transition from the ICU to the medical/surgical unit. Secondary outcomes of the study included meropenem total DOT, total number of meropenem doses after transfer to the medical unit, 30-day all-cause mortality, and 30-day readmission. Results A total of 163 patients were evaluated in both the pre-intervention (n = 87) and post-intervention groups (n = 76). Median meropenem DOT after transition of care (3 days vs. 2 days, P = 0.0004) and number of meropenem doses after transition (6 doses vs. 4 doses, P = 0.014) were significantly lower after TOC intervention implementation. However, total meropenem DOTs were not different at 5 days in both groups. Recommendations for de-escalation or discontinuation were accepted 60% of the time among providers. Conclusion An EMR-based ASP intervention did decrease meropenem DOT after patients were transitioned from the ICU to the medical/surgical floors. Results of the meropenem EMR-based ASP intervention may be used to expand to other broad-spectrum antimicrobials/antifungals in patients transitioning levels of care. Disclosures All Authors: No reported disclosures

Heart rate as a marker of relapse during withdrawal of heart failure therapy in patients with recovered dilated cardiomyopathy: an analysis from TRED-HF

Introduction In TRED-HF, 40% of patients with recovered dilated cardiomyopathy (DCM) relapsed in the short-term during phased withdrawal of drug therapy. Non-invasive markers of relapse may be used to monitor patients who wish a trial of therapy withdrawal and provide insights into the pathophysiological drivers of relapse. Purpose To investigate the relationship between changes in heart rate (HR) and relapse amongst patients with recovered DCM undergoing therapy withdrawal in TRED-HF. Methods Patients with recovered DCM were randomised to phased withdrawal of therapy or to continue therapy for 6 months. After 6 months of continued therapy, those in the control arm underwent withdrawal of therapy in a single arm crossover phase. HR was measured at each study visit. Mean HR and 95% confidence intervals (CI) were calculated at baseline, 45 days after baseline, 45 days prior to the end of the study or relapse and at the end of the study or relapse. Patients were stratified by treatment arm and the occurrence of the primary relapse end-point. Heart rate at follow-up was compared amongst patients who had therapy withdrawn and relapsed versus those who had therapy withdrawn and did not. ANCOVA was used to adjust for differences in HR at baseline between the two groups. Results Of 51 patients randomised, 26 were assigned to continue therapy and 25 to withdraw therapy. In the randomised and cross-over phases, 20 patients met the primary relapse end-point; one patient withdrew from the study and one patient completed follow-up in the control arm but did not enter the cross-over phase. Mean HR (standard deviation) at baseline and follow-up for (i) patients in the control arm was 69.9 (9.8) & 65.9 (9.1) respectively; (ii) for those who had therapy withdrawn and did not relapse was 64.6 (10.7) & 74.7 (10.4) respectively; and (iii) for those who had therapy withdrawn and relapsed was 68.3 (11.3) & 86.1 (11.8) respectively [all beats per minute]. The mean change in HR between the penultimate visit and the final visit for those who had therapy withdrawn and did not relapse was −2.4 (9.7) compared to 3.1 (15.5) for those who relapsed. After adjusting for differences in HR at baseline, the mean difference in HR measured at follow-up between patients who underwent therapy withdrawal and did, and did not relapse was 10.4bpm (95% CI 4.0–16.8; p=0.002) (Figure 1 & Table 1). Conclusion(s) A larger increase in HR may be a simple and effective marker of relapse for patients with recovered DCM who have insisted on a trial of therapy withdrawal. Whether HR control is crucial to the maintenance of remission amongst patients with improved cardiac function, or is simply a marker of deteriorating cardiac function, warrants further investigation. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): British Heart Foundation

Maintaining treatment volumes during the COVID-19 pandemic.

103 Background: Uninterrupted care is essential for optimal outcomes in cancer care. The COVID-19 pandemic presented numerous challenges in providing continuity of care for many facilities. Our practice was able to deliver ongoing treatment for a large volume of our patients while maintaining a safe environment. Methods: A practice-wide effort to continue therapy in cancer patients undergoing active treatment began in March 2020 as the peak of the pandemic was beginning in Tennessee. Those patients who were receiving active treatment continued the planned treatment while reducing non-acute treatment visits. We assessed the volume of patients receiving treatments in our facilities for two periods: JanuaryDecember 2019 and January-May 2020. We compared the aggregate number of chemotherapy infusions, therapeutic infusions and injections as well as total treatments. Results: Overall, treatments remained relatively stable without a significant change in treatment volumes. There was a 3.69% decline in total treatment with therapeutic infusions (-9.68%) and injections (-7.85%) which accounted for the majority of deferred treatments. Chemotherapy infusions remained stable with an average increase (1.90%) in treatments. Conclusions: During the COVID-19 pandemic, our facility was able to maintain stable treatment numbers while providing safe care to our patients. We had no known diagnosed COVID-19 cases from potential exposures in our clinics. Decreases in treatment reflected less critical therapies. There did seem to be a delay for chemotherapy/immunotherapy that seemed to resolve as the peak passed for this region. Offloading of less critical treatments can result in continued treatment of cancer patients during a pandemic. [Table: see text]

Psychiatric, psychological and ethical determinants of the phenomenon of self-stigmatization of mental illness – literature review

Introduction: In psychiatry and psychology stigmatization consists in labelling a person suffering from a disorder with the stigma of mental illness, associated with numerous negative stereotypes that are established in both individual and social mentality.Objective: The aim of the present article is to present the phenomenon of self-stigma from the perspective of psychiatric patients, including patients suffering from schizophrenia, to scientific consideration.The state of knowledge: The available data on this subject suggests that schizophrenia is particularly stigmatized, and the degree of stigmatization of patients with this diagnosis is worsening. Self-stigma plays a significant role in various areas of patients’ lives, sometimes discouraging them to continue therapy. Psychiatric patients have to face not only the symptoms of their disorders, but also stigmatization. In the event patient’s self-stigmatization of mental illness occurs, a responsible psychiatrist and psychologist conducting the therapy has the moral obligation to supervise the process of psychiatric and psychological assistance in the context of the aforelisted issues.Conclusions: The problem of self-stigmatization of a psychiatric patients is a topical issue that is well worth further exploration in order to better understand and help patients more effectively.

Ten-day decitabine with venetoclax (DEC10-VEN) in AML and high-risk (HR) MDS.

7519 Background: VEN-based low intensity regimens have shown promise in older pts with newly diagnosed (ND) AML. We hypothesized that adding VEN to 10-day (d) DEC may improve outcomes in AML and HR MDS. Methods: Pts received VEN 400 mg daily or equivalent with DEC 20 mg/m2 for 10d every 4-8 weeks for induction and DEC 5d with VEN for consolidation after CR/CRi. If cycle 1 day 21 bone marrow showed ≤5% blasts, VEN was held to enable count recovery. VEN duration could be further reduced for myelosuppression. FLT3 and IDH inhibitors were allowed for applicable pts. All pts received tumor lysis syndrome (TLS) prophylaxis. Primary objective was overall response rate (ORR). Secondary objectives were safety and overall survival (OS). Data cut-off date was February 6, 2020. Results: Between January 2018 and December 2019 we enrolled 184 pts with ND AML (>60 yrs), untreated secondary AML (sAML), treated sAML, relapsed/refractory (R/R) AML and HR MDS (Table). 58% pts were ≥70 yrs, 30% pts had ECOG PS ≥2, 67% pts had ELN adverse risk AML. Previously treated pts (n=96) had received a median of 1 prior therapy (range 1-8) including HMA (62), intensive chemotherapy (49) and stem cell transplantation (SCT, 27). 30d mortality was 3.3% and 60d mortality was 7.6%. 30d mortality in ND AML was 1.4%. Most common G3/4 adverse events were infections with G3/4 neutropenia (46%), febrile neutropenia (28%), infections with ANC ≥1x109/L (6%) and TLS (3%). Outcomes are shown in Table. 25 pts (14%) proceeded to SCT including treatment naive AML (ND+ untreated sAML, 12), previously treated AML (treated sAML + R/R, 11) and HR MDS (2). 100d post-SCT mortality was 4%. Median OS in treatment naïve AML pts undergoing SCT was not reached (1yr OS 100%) and for previously treated AML pts was 22.1 months (mo). After a median follow up of 15 mos, 25% PTS continue therapy. Additional analyses by molecular subgroups will be presented. Conclusions: DEC10-VEN is safe and highly effective in ND AML and can serve as an effective bridge to SCT in previously treated pts. Trial continues to accrue (NCT03404193). Clinical trial information: NCT03404193 . [Table: see text]

Onset, duration, and clinical impact of immune-related adverse events in Hodgkin lymphoma.

95 Background: The incidence of immune-related adverse events (irAEs) in patients (pts) with Hodgkin lymphoma (HL) treated with PD-1 antibodies (ICI) is reported at 28 - 36%. However, clinically relevant information on irAE onset, duration, or impact on ability to continue therapy in HL is lacking. Additionally, these incidence rates reflect CTCAE definition and grading, and not ASCO Clinical Practice Guidelines irAE-specific criteria (Brahmer et al, JCO 2018). The objectives of this study were to evaluate the rate and severity of irAEs in HL pts using ASCO criteria, to characterize irAE time profile and to assess their impact on continued therapy. Methods: HL pts who received a PD-1 inhibitor for the treatment of HL at Mayo Clinic Rochester between January 1, 2011 and March 1, 2018 were identified. We conducted a detailed, longitudinal retrospective chart review with definition and grading of irAEs in accordance with ASCO guidelines. Results: Fifty-one pts were identified (35% women, median age at ICI initiation 35 years [range: 19-87]). Median duration of follow up from ICI start was 30 months (range: 1-70). Thirty-one pts (61%) had any irAE. Most common irAEs were inflammatory/bullous dermatoses (23.5%/5.9% any grade/grade3-4; median onset/duration of 81/57 days[d]), followed by thyroiditis (22%/0%; 86/84 d), colitis (14%/8%; 82/106 d), pneumonitis (14%/10%; 241/182 d), and hepatitis (14%/4%; 71/35 d). Fifteen pts (29%) required treatment with steroids. Among the total cohort, ICI was held for an irAE 28 times (50% of 56 total irAEs). Median treatment cycles held was 2.5 and ICI was permanently discontinued due to irAE in 18%. The most common irAE leading to treatment discontinuation was pneumonitis, followed by neuritis (5.9%/3.9%; 179/374 d), colitis, and rash. Conclusions: The rate of irAEs of 61% in this cohort as defined by ASCO consensus criteria was higher than reported in trials. Most irAEs were characterized by delayed onset of several months and prolonged duration, particularly pneumonitis and neuritis. Treatment discontinuation due to irAEs was infrequent overall. Further studies are needed to determine whether the development or duration of irAEs is predictive of treatment outcomes in HL.

RECIST v1.1 and irRECIST outcomes in advanced HCC treated with pembrolizumab (pembro).

528 Background: IO can cause pseudoprogression (PP): apparent tumor growth followed by stability or favorable response. We assess PP in aHCC treated with pembro (KEYNOTE-224 [ph 2], NCT02702414; KEYNOTE-240 [ph 3], NCT02702401). Methods: aHCC pts with PD on/intolerance to sorafenib received pembro 200 mg IV Q3W until unacceptable toxicity, study withdrawal, 2 y of therapy, or RECIST v1.1 PD; if pt clinically stable at PD, physician could continue therapy and repeat scans to confirm PD per irRECIST. PP=RECIST v1.1 PD then irRECIST response other than PD. Data cutoff: Jan 02, 2019 (KEYNOTE-240); Feb 13, 2018 (KEYNOTE-224). Results: 245/382 pembro-treated pts had RECIST v1.1 PD: 138 irRECIST repeat scan; 105 PD; 33 (8.6%; 33/382) outcomes other than PD. Of 33 PP, 29 had SD, 3 PR, 1 CR (irRECIST; 29 had this at first irRECIST scan; 4 [2 SD, 2 PR] at subsequent scan). For initial RECIST v1.1 PD, 16/33 PP had PD at first postbaseline scan (pembro cycles 2-4); 17/33 PP had PD at pembro cycles 4-18. Median (range) time to RECIST v1.1 PD in the 33 PP was 80 (37-378) days. OS shown in Table. KEYNOTE-240 had 135 PBO-treated pts: 8 (5.9%) PP; small samples bar meaningful interpretation. Conclusions: PP in aHCC, per irRECIST, has a similar incidence to other cancers (eg, melanoma) and does not seem to correlate with OS. Data may help physicians assess when to continue pembro after PD. Clinical trial information: NCT02702414, NCT02702401. [Table: see text]