Gender Representation of Health Care Professionals in Large Language Model-Generated Stories.

Importance: With the growing use of large language models (LLMs) in education and health care settings, it is important to ensure that the information they generate is diverse and equitable, to avoid reinforcing or creating stereotypes that may influence the aspirations of upcoming generations. Objective: To evaluate the gender representation of LLM-generated stories involving medical doctors, surgeons, and nurses and to investigate the association of varying personality and professional seniority descriptors with the gender proportions for these professions. Design, Setting, and Participants: This is a cross-sectional simulation study of publicly accessible LLMs, accessed from December 2023 to January 2024. GPT-3.5-turbo and GPT-4 (OpenAI), Gemini-pro (Google), and Llama-2-70B-chat (Meta) were prompted to generate 500 stories featuring medical doctors, surgeons, and nurses for a total 6000 stories. A further 43 200 prompts were submitted to the LLMs containing varying descriptors of personality (agreeableness, neuroticism, extraversion, conscientiousness, and openness) and professional seniority. Main Outcomes and Measures: The primary outcome was the gender proportion (she/her vs he/him) within stories generated by LLMs about medical doctors, surgeons, and nurses, through analyzing the pronouns contained within the stories using χ2 analyses. The pronoun proportions for each health care profession were compared with US Census data by descriptive statistics and χ2 tests. Results: In the initial 6000 prompts submitted to the LLMs, 98% of nurses were referred to by she/her pronouns. The representation of she/her for medical doctors ranged from 50% to 84%, and that for surgeons ranged from 36% to 80%. In the 43 200 additional prompts containing personality and seniority descriptors, stories of medical doctors and surgeons with higher agreeableness, openness, and conscientiousness, as well as lower neuroticism, resulted in higher she/her (reduced he/him) representation. For several LLMs, stories focusing on senior medical doctors and surgeons were less likely to be she/her than stories focusing on junior medical doctors and surgeons. Conclusions and Relevance: This cross-sectional study highlights the need for LLM developers to update their tools for equitable and diverse gender representation in essential health care roles, including medical doctors, surgeons, and nurses. As LLMs become increasingly adopted throughout health care and education, continuous monitoring of these tools is needed to ensure that they reflect a diverse workforce, capable of serving society's needs effectively.

Antithrombotic utilization, adverse events, and associations with treatment outcomes in multiple myeloma: pooled analysis of three clinical trials.

Background: Patients with multiple myeloma (MM) are at risk of venous thromboembolism (VTE), worsened by immunomodulatory drugs. Although antithrombotics are recommended for prophylaxis, existing guidelines are suboptimal and treatment outcomes remain unclear. Objectives: This study aimed to investigate adverse events, antithrombotic utilization, and their associations with survival outcomes in patients with MM initiating multi-drug immunomodulatory combinations. Design: A posthoc analysis of individual-participant level data (IPD). Methods: IPD from three daratumumab clinical trials (MAIA, POLLUX, and CASTOR) were pooled. Adverse events incidence and antithrombotic utilization were assessed. Logistic and Cox regression were utilized to examine associations between antithrombotics use with adverse events and survival outcomes at the baseline and 6-month landmark. Results: Among 1804 patients, VTE occurred in 10%, bleeding in 14%, ischemic heart disease in 4%, and stroke in 2%. Patients with these adverse events demonstrated elevated rates of any grade ⩾3 events. Antiplatelet (primarily aspirin) and anticoagulant (primarily LMWH and direct oral anticoagulants) prescriptions have seen an increase from baseline (25% and 14%, respectively) to 6 months (35% and 31%). The primary indication for their use was prophylaxis. Anticoagulant use within 6 months was associated with reduced VTE (OR (95% CI) = 0.45 (0.26-0.77), p = 0.004), while antiplatelet use showed no associations with any evaluated adverse events. Antithrombotics and survival outcomes had no significant associations. Conclusion: This study underscores the complexities of antithrombotic therapy and adverse events in MM and highlights the need for vigilant and proactive management due to increased grade ⩾3 adverse events. While anticoagulant use was associated with reduced VTE risk, further research is needed to optimize thromboprophylaxis guidelines and explore antithrombotic efficacy and safety in patients with MM. Trial registration: MAIA (NCT02252172), POLLUX (NCT02076009), CASTOR (NCT02136134).

Blood clot prevention drugs in multiple myeloma: usage and impact on patient outcomes Aims and Purpose of the Research This study aimed to understand how blood-thinning medications are used by patients with multiple myeloma, a type of blood cancer. Specifically, we wanted to find out how often these medications are used, what side effects they might cause, and whether they are linked with how long the patients live. Background of the Research This study is important because patients with multiple myeloma often have a higher risk of blood clots, especially when they are taking certain anticancer treatments. Blood-thinning drugs are usually recommended to prevent these clots, but it's not always clear how well these drugs work or what side effects they might cause. Methods and Research Design This study looked at data from three clinical trials involving a multiple myeloma drug called daratumumab. We looked at how often side effects occurred and how often blood-thinning drugs were used. Two groups of blood thinning drugs were investigated: antiplatelets and anticoagulants. We used two types of statistical methods, called logistic and Cox regression, to see if there was a connection between the use of these blood-thinning drugs and the occurrence of side effects or survival rates at the start of the study and after six months. Results and Importance The study found that the use of blood-thinning drugs increased over time and that using anticoagulants within the first six months was linked to a lower risk of blood clots. However, blood-thinning drugs were not linked with how long the patients lived. These results are important because they can help doctors better manage the use of blood-thinning drugs in patients with multiple myeloma. The key message is that more research is needed to improve guidelines for preventing blood clots and to better understand the safety and effectiveness of blood-thinning drugs in these patients.

Establishing the capacity to monitor proteins relevant to the study of drug exposure and response using liver-derived extracellular vesicles.

AIMS: Drug exposure and response is determined by pharmacokinetic (PK) and pharmacodynamic (PD) profiles. Interindividual differences in abundance of drug metabolizing enzymes (DMEs) and drug target proteins underpin PK and PD variability and impact treatment efficacy and tolerability. Extracellular vesicles (EVs) carry protein cargo inherited from originating cells and may be useful for defining differences in key proteins related to hepatic drug metabolism and the treatment of metabolic-associated fatty liver disease (MAFLD). We sought to quantify these proteins in liver-derived EVs and establish the profile relative to paired tissue. METHODS: EVs were recovered from human liver tissue samples (LT-EV, n = 11). Targeted liquid chromatography with tandem mass spectrometry (LC-MS/MS) assays were employed for absolute quantification of proteins in EV isolates and matched liver tissue. RESULTS: DMEs and MAFLD drug targets were readily detected and quantified in LT-EVs. Twelve of 15 DMEs exhibited moderate to strong correlation (Spearman ⍴ = 0.618-0.973) between tissue and EVs. Correlation in protein abundance was influenced by the extent of extra-hepatic expression of the target. CONCLUSIONS: This study provides evidence that key proteins related to PK and PD profiles can be measured in liver-derived EVs and abundance of liver-enriched DMEs are robustly correlated between paired tissue and EVs. The robust detection of protein markers related to drug PD profile in MAFLD opens the possibility to track within-subject changes in MAFLD and lays the foundation for future development of a liver-derived EV liquid biopsy to assess markers of drug exposure and response in vivo.

Clinical Study Report and Individual Participant Data Transparency for US Food and Drug Administration-Approved Anticancer Drugs: A Call for Systematic Data Availability.

Unlocking the full potential of clinical trials through comprehensive CSR and IPD sharing can revolutionize cancer care, enhance safety evaluations, and reduce bias in systematic reviews. It is time for all stakeholders to embrace transparency and advance patient-centered outcomes.

A lack of association between BMI and chemoimmunotherapy efficacy in advanced non-small cell lung cancer: Secondary analysis of the IMpower150 and IMpower130 clinical trials.

BACKGROUND: Multiple studies have indicated that patients with high body mass index (BMI) may have favourable survival outcomes following treatment with an immune checkpoint inhibitor (ICI). However, this evidence is limited by several factors, notably the minimal evidence from randomised controlled trials (RCTs), the use of categorised BMI with inconsistent cut point definitions, and minimal investigation of contemporary combination ICI therapy. Moreover, whether overweight and obese patients gain a larger benefit from contemporary frontline chemoimmunotherapy in non-small cell lung cancer (NSCLC) is unclear. METHODS: This secondary analysis pooled individual patient data from the intention-to-treat population of the IMpower130 and IMpower150 RCTs comparing chemoimmunotherapy versus chemotherapy. Co-primary outcomes were overall survival (OS) and progression-free survival (PFS). The potentially non-linear relationship between BMI and chemoimmunotherapy treatment effect was evaluated using Multivariable Fractional Polynomial Interaction (MFPI). As a sensitivity analysis, chemoimmunotherapy treatment effect (chemoimmunotherapy versus chemotherapy) on survival was also estimated for each BMI subgroup defined by World Health Organisation classification. Exploratory analyses in the respective chemoimmunotherapy and chemotherapy cohort were undertaken to examine the survival outcomes among BMI subgroups. RESULTS: A total of 1282 patients were included. From the MFPI analysis, BMI was not significantly associated with chemoimmunotherapy treatment effect with respect to either OS (p = 0.71) or PFS (p = 0.35). This was supported by the sensitivity analyses that demonstrated no significant treatment effect improvement in OS/PFS among overweight or obese patients compared to normal weight patients (OS: normal BMI HR = 0.74 95% CI 0.59-0.93, overweight HR = 0.78 95% CI 0.61-1.01, obese HR = 0.84 95% CI 0.59-1.20). Exploratory analyses further highlighted that survival outcomes were not significantly different across BMI subgroups in either the chemoimmunotherapy therapy cohort (Median OS: normal BMI 19.9 months, overweight 17.9 months, and obese 19.5 months, p = 0.7) or the chemotherapy cohort (Median OS: normal 14.1 months, overweight 15.9 months, and obese 16.7 months, p = 0.7). CONCLUSION: There was no association between high BMI (overweight or obese individuals) and enhanced chemoimmunotherapy treatment benefit in front-line treatment of advanced non-squamous NSCLC. This contrasts with previous publications that showed a superior treatment benefit in overweight and obese patients treated with immunotherapy given without chemotherapy.

Current safeguards, risk mitigation, and transparency measures of large language models against the generation of health disinformation: repeated cross sectional analysis.

OBJECTIVES: To evaluate the effectiveness of safeguards to prevent large language models (LLMs) from being misused to generate health disinformation, and to evaluate the transparency of artificial intelligence (AI) developers regarding their risk mitigation processes against observed vulnerabilities. DESIGN: Repeated cross sectional analysis. SETTING: Publicly accessible LLMs. METHODS: In a repeated cross sectional analysis, four LLMs (via chatbots/assistant interfaces) were evaluated: OpenAI's GPT-4 (via ChatGPT and Microsoft's Copilot), Google's PaLM 2 and newly released Gemini Pro (via Bard), Anthropic's Claude 2 (via Poe), and Meta's Llama 2 (via HuggingChat). In September 2023, these LLMs were prompted to generate health disinformation on two topics: sunscreen as a cause of skin cancer and the alkaline diet as a cancer cure. Jailbreaking techniques (ie, attempts to bypass safeguards) were evaluated if required. For LLMs with observed safeguarding vulnerabilities, the processes for reporting outputs of concern were audited. 12 weeks after initial investigations, the disinformation generation capabilities of the LLMs were re-evaluated to assess any subsequent improvements in safeguards. MAIN OUTCOME MEASURES: The main outcome measures were whether safeguards prevented the generation of health disinformation, and the transparency of risk mitigation processes against health disinformation. RESULTS: Claude 2 (via Poe) declined 130 prompts submitted across the two study timepoints requesting the generation of content claiming that sunscreen causes skin cancer or that the alkaline diet is a cure for cancer, even with jailbreaking attempts. GPT-4 (via Copilot) initially refused to generate health disinformation, even with jailbreaking attempts-although this was not the case at 12 weeks. In contrast, GPT-4 (via ChatGPT), PaLM 2/Gemini Pro (via Bard), and Llama 2 (via HuggingChat) consistently generated health disinformation blogs. In September 2023 evaluations, these LLMs facilitated the generation of 113 unique cancer disinformation blogs, totalling more than 40 000 words, without requiring jailbreaking attempts. The refusal rate across the evaluation timepoints for these LLMs was only 5% (7 of 150), and as prompted the LLM generated blogs incorporated attention grabbing titles, authentic looking (fake or fictional) references, fabricated testimonials from patients and clinicians, and they targeted diverse demographic groups. Although each LLM evaluated had mechanisms to report observed outputs of concern, the developers did not respond when observations of vulnerabilities were reported. CONCLUSIONS: This study found that although effective safeguards are feasible to prevent LLMs from being misused to generate health disinformation, they were inconsistently implemented. Furthermore, effective processes for reporting safeguard problems were lacking. Enhanced regulation, transparency, and routine auditing are required to help prevent LLMs from contributing to the mass generation of health disinformation.

Immunotherapy for advanced non-small cell lung cancer with negative programmed death-ligand 1 expression: a literature review.

Background and Objective: Lung cancer, mainly non-small cell lung cancer (NSCLC), is a serious threat to human life. In particular, the prognosis for advanced patients is poor, with the 5-year survival rate being exceedingly low. In recent years, immune checkpoint inhibition has changed the pattern of the treatment of a variety of cancers, including lung cancer; however, not all patients can benefit from immunotherapy, and thus finding the right biomarkers is particularly important for guiding precise treatment. Programmed death-ligand 1 (PD-L1) expression is one of the most valuable biomarkers for predicting the efficacy of lung cancer immunotherapy. Several studies have confirmed that patients with high PD-L1 expression are more likely to benefit from immunotherapy, but there is a high proportion of people with negative PD-L1 expression constituting a patient population that cannot be ignored. This article reviews the distribution of PD-L1 expression, the methods for evaluating PD-L1, and the effectiveness of immunotherapy for advanced NSCLC with negative PD-L1 expression. Methods: We performed a literature review to identify relevant data published until September 2022. In order to organize related information, we searched for literature in PubMed; abstracts and reports published in the American Society of Clinical Oncology (ASCO), the European Society for Medical Oncology (ESMO), the World Conference on Lung Cancer (WCLC), and other congresses; and clinical trial information registered on ClinicalTrials.gov. Information on the distribution of PD-L1 expression, detection of PD-L1, and immunotherapy efficacy for NSCLC with negative PD-L1 expression was collated and reviewed. Key Content and Findings: The incidence of PD-L1 expression in patients with stage IIIB/IV NSCLC is similar in all regions of the world, but PD-L1 expression level is associated with certain clinicopathological features. The expression of PD-L1 can be evaluated by various detecting methods. Some immunotherapy regimens have better efficacy than traditional chemotherapy in patients with negative PD-L1 expression. Conclusions: Patients with NSCLC and negative PD-L1 expression can receive better survival benefits under some immunotherapy types, and these may represent a better treatment option for this relatively small patient population.

Association of proton pump inhibitor use with survival and adverse effects outcomes in patients with multiple myeloma: pooled analysis of three clinical trials.

Proton pump inhibitors (PPIs) are commonly used in cancer patients, but their impact on treatment outcomes in multiple myeloma (MM) patients remains unclear. This study investigated the association of PPI use with survival and adverse effects in MM patients across three randomized-control trials initiating daratumumab, lenalidomide, or bortezomib combination treatments. Cox proportional hazard analysis and logistic regression were employed to assess the associations with treatment outcomes, while adjusting for age, sex, weight, MM international staging system stage, ECOG-performance status, comorbidity count, and presence of gastrointestinal disorders. Pooled data involving 1804 patients revealed that 557 (32%) used PPIs at baseline. PPI use was independently associated with worse overall survival (adjusted HR [95% CI] 1.32 [1.08-1.62], P = 0.007) and grade ≥ 3 adverse events (adjusted OR [95% CI] 1.39 [1.03-1.88], P = 0.030). However, the association with progression-free survival did not reach statistical significance (adjusted HR [95% CI] 1.14 [0.97-1.33], P = 0.112). Findings were consistent across trials and treatment arms. PPI use was identified as a negative prognostic factor in MM patients, potentially enhancing clinical decisions regarding its use. Further research is needed to fully comprehend the impacts and safety of PPI use in MM patients.

Accessibility of clinical study reports supporting medicine approvals: a cross-sectional evaluation.

OBJECTIVES: Clinical study reports (CSRs) are highly detailed documents that play a pivotal role in medicine approval processes. Though not historically publicly available, in recent years, major entities including the European Medicines Agency (EMA), Health Canada, and the US Food and Drug Administration (FDA) have highlighted the importance of CSR accessibility. The primary objective herein was to determine the proportion of CSRs that support medicine approvals available for public download as well as the proportion eligible for independent researcher request via the study sponsor. STUDY DESIGN AND SETTING: This cross-sectional study examined the accessibility of CSRs from industry-sponsored clinical trials whose results were reported in the FDA-authorized drug labels of the top 30 highest-revenue medicines of 2021. We determined (1) whether the CSRs were available for download from a public repository, and (2) whether the CSRs were eligible for request by independent researchers based on trial sponsors' data sharing policies. RESULTS: There were 316 industry-sponsored clinical trials with results presented in the FDA-authorized drug labels of the 30 sampled medicines. Of these trials, CSRs were available for public download from 70 (22%), with 37 available at EMA and 40 at Health Canada repositories. While pharmaceutical company platforms offered no direct downloads of CSRs, sponsors confirmed that CSRs from 183 (58%) of the 316 clinical trials were eligible for independent researcher request via the submission of a research proposal. Overall, 218 (69%) of the sampled clinical trials had CSRs available for public download and/or were eligible for request from the trial sponsor. CONCLUSION: CSRs were available from 69% of the clinical trials supporting regulatory approval of the 30 medicines sampled. However, only 22% of the CSRs were directly downloadable from regulatory agencies, the remaining required a formal application process to request access to the CSR from the study sponsor.

Health Disinformation Use Case Highlighting the Urgent Need for Artificial Intelligence Vigilance: Weapons of Mass Disinformation.

Importance: Although artificial intelligence (AI) offers many promises across modern medicine, it may carry a significant risk for the mass generation of targeted health disinformation. This poses an urgent threat toward public health initiatives and calls for rapid attention by health care professionals, AI developers, and regulators to ensure public safety. Observations: As an example, using a single publicly available large-language model, within 65 minutes, 102 distinct blog articles were generated that contained more than 17 000 words of disinformation related to vaccines and vaping. Each post was coercive and targeted at diverse societal groups, including young adults, young parents, older persons, pregnant people, and those with chronic health conditions. The blogs included fake patient and clinician testimonials and obeyed prompting for the inclusion of scientific-looking referencing. Additional generative AI tools created an accompanying 20 realistic images in less than 2 minutes. This process was undertaken by health care professionals and researchers with no specialized knowledge in bypassing AI guardrails, relying solely on publicly available information. Conclusions and Relevance: These observations demonstrate that when the guardrails of AI tools are insufficient, the ability to rapidly generate diverse and large amounts of convincing disinformation is profound. Beyond providing 2 example scenarios, these findings demonstrate an urgent need for robust AI vigilance. The AI tools are rapidly progressing; alongside these advancements, emergent risks are becoming increasingly apparent. Key pillars of pharmacovigilance-including transparency, surveillance, and regulation-may serve as valuable examples for managing these risks and safeguarding public health.

Objective response rate and progression-free survival as surrogates for overall survival treatment effect: A meta-analysis across diverse tumour groups and contemporary therapies.

BACKGROUND: Overall survival (OS) results from randomized control trials (RCT) provide the strongest evidence for efficacy of anti-cancer treatments but can take a considerable amount of time to mature. Progression free survival (PFS) and objective response rate (ORR) are used as an early surrogate of OS treatment effect however their validity remains unclear. Our study aims to comprehensively evaluate ORR and PFS as surrogates for OS treatment effect across tumor groups and treatment types. MATERIAL AND METHODS: Phase 3 RCTs in solid malignancies that reported OS/PFS and ORR published between 1st of January 2010 and 30th of June 2022 were evaluated. The relationship of surrogate endpoints and OS treatment effect was assessed via weighted linear regression. The coefficient of determination (R2) quantified the fit of the regression model. RESULTS: 675 phase 3 RCT comprising of 350 112 patients were analysed. ORR (R2 of 0.10) and PFS (R2 of 0.38) were poor surrogate markers of OS treatment effect. The strength of surrogacy differed within treatment and tumour groups. PFS had the highest R2 for chemotherapy (0.56) and lowest for targeted therapy (0.40). PFS had the highest level of surrogacy for melanoma (R2 = 0.72) and pancreatic cancer (R2 = 0.70) compared to other tumour groups. Importantly ORR and PFS were also poorly correlated to each other (R2 = 0.33). CONCLUSIONS: ORR and PFS were poor trial-level surrogate markers of OS. The surrogacy performance of ORR and PFS differed by treatment and malignancy sub-type.

Proteomic profiling of paired human liver homogenate and tissue derived extracellular vesicles.

Advances in technologies to isolate extracellular vesicles (EVs) and detect/quantify their cargo underpin the novel potential of these circulating particles as a liquid biopsy to understand physiology and disease. One organ of particular interest in terms of utilizing EVs as a liquid biopsy is the liver. The extent to which EVs originating from the liver reflect the functional status of this organ remains unknown. This is an important knowledge gap that underpins the utility of circulating liver derived EVs as a liquid biopsy. The primary objective of this study was to characterize the proteomic profile of EVs isolated from the extracellular space of liver tissue (LEV) and compare this profile to that of paired tissue (LH). LCMS analyses detected 2892 proteins in LEV and 2673 in LH. Of the 2673 proteins detected in LH, 1547 (58%) were also detected in LEV. Bioinformatic analyses demonstrated comparable representation of proteins in terms of biological functions and cellular compartments. Although, enriched representation of membrane proteins and associated functions was observed in LEV, while representation of nuclear proteins and associated functions was depleted in LEV. These data support the potential use of circulating liver derived EVs as a liquid biopsy for this organ.

Heterogeneity and Utility of Pharmaceutical Company Sharing of Individual-Participant Data Packages.

Importance: The pharmaceutical industry has made substantial investments in developing processes for sharing individual-participant data (IPD) from clinical trials. However, the utility and completeness of shared IPD and supporting documents must be evaluated to ensure the potential for scientific advancements from the data sharing ecosystem can be realized. Objective: To assess the utility and completeness of IPD and supporting documents provided from industry-sponsored clinical trials. Design, Setting, and Participants: From February 9, 2022, to February 9, 2023, 91 of 203 clinical trials supporting US Food and Drug Administration registrations of anticancer medicines for the treatment of solid tumors from the past decade were confirmed as eligible for IPD request. This quality improvement study performed a retrospective audit of the utility and completeness of the IPD and supporting documents provided from the 91 clinical trials for a planned meta-analysis. Exposures: Request for IPD from 91 clinical oncology trials indicated as eligible for the request. Main Outcomes and Measures: The utility and completeness of the IPD and supporting documents provided. Results: The IPD packages were obtained from 70 of 91 requested clinical trials (77%). The median time to data provision was 123 (range, 117-352) days. Redactions were observed in 18 of the acquired IPD packages (26%) for outcome data, 11 (16%) for assessment variables, and 19 (27%) for adjustment data. Additionally, 20 IPD packages (29%) lacked a clinical study report, 4 (6%) had incomplete or missing data dictionaries, and 20 (29%) were missing anonymization or redaction description files. Access to IPD from 21 eligible trials (23%) was not granted. Conclusions and Relevance: In this quality improvement study, there was substantial variability within the provided IPD packages regarding the completeness of key data variables and supporting documents. To improve the data sharing ecosystem, key areas for enhancement include (1) ensuring that clinical trials are eligible for IPD sharing, (2) making eligible IPD transparently accessible, and (3) ensuring that IPD packages meet a standard of utility and completeness.

A 10-year update to the principles for clinical trial data sharing by pharmaceutical companies: perspectives based on a decade of literature and policies.

Data sharing is essential for promoting scientific discoveries and informed decision-making in clinical practice. In 2013, PhRMA/EFPIA recognised the importance of data sharing and supported initiatives to enhance clinical trial data transparency and promote scientific advancements. However, despite these commitments, recent investigations indicate significant scope for improvements in data sharing by the pharmaceutical industry. Drawing on a decade of literature and policy developments, this article presents perspectives from a multidisciplinary team of researchers, clinicians, and consumers. The focus is on policy and process updates to the PhRMA/EFPIA 2013 data sharing commitments, aiming to enhance the sharing and accessibility of participant-level data, clinical study reports, protocols, statistical analysis plans, lay summaries, and result publications from pharmaceutical industry-sponsored trials. The proposed updates provide clear recommendations regarding which data should be shared, when it should be shared, and under what conditions. The suggested improvements aim to develop a data sharing ecosystem that supports science and patient-centred care. Good data sharing principles require resources, time, and commitment. Notwithstanding these challenges, enhancing data sharing is necessary for efficient resource utilization, increased scientific collaboration, and better decision-making for patients and healthcare professionals.

Time to deterioration of patient-reported outcomes as a surrogate of overall survival: a meta-analysis.

BACKGROUND: Overall survival is the optimal marker of treatment efficacy in randomized clinical trials (RCTs) but can take considerable time to mature. Progression-free survival (PFS) has served as an early surrogate of overall survival but is imperfect. Time to deterioration in quality of life (QOL) measures could be a surrogate for overall survival. METHODS: Phase 3 RCTs in solid malignancies that reported overall survival, PFS, and time to deterioration in QOL or physical function published between January 1, 2010, and June 30, 2022, were evaluated. Weighted regression analysis was used to assess the relationship between PFS, time to deterioration in QOL, and time to deterioration in physical function with overall survival. The coefficient of determination (R2) was used to quantify surrogacy. RESULTS: In total, 138 phase 3 RCTs were included. Of these, 47 trials evaluated immune checkpoint inhibitors and 91 investigated non-immune checkpoint inhibitor agents. Time to deterioration in QOL (137 RCTs) and time to deterioration in physical function (75 RCTs) performed similarly to PFS as surrogates for overall survival (R2 = 0.18 vs R2 = 0.19 and R2 = 0.10 vs R2 = 0.09, respectively). For immune checkpoint inhibitor studies, time to deterioration in physical function had a higher association with overall survival than with PFS (R2 = 0.38 vs R2 = 0.19), and PFS and time to deterioration in physical function did not correlate with each other (R2 = 0). When time to deterioration in physical function and PFS are used together, the coefficient of determination increased (R2 = 0.57). CONCLUSIONS: Time to deterioration in physical function appears to be an overall survival surrogate measure of particular importance for immune checkpoint inhibitor treatment efficacy. The combination of time to deterioration in physical function with PFS may enable better prediction of overall survival treatment benefit in RCTs of immune checkpoint inhibitors than either PFS or time to deterioration in physical function alone.

Prediction of Prostate Cancer Biochemical and Clinical Recurrence Is Improved by IHC-Assisted Grading Using Appl1, Sortilin and Syndecan-1.

Gleason scoring is used within a five-tier risk stratification system to guide therapeutic decisions for patients with prostate cancer. This study aimed to compare the predictive performance of routine H&E or biomarker-assisted ISUP (International Society of Urological Pathology) grade grouping for assessing the risk of biochemical recurrence (BCR) and clinical recurrence (CR) in patients with prostate cancer. This retrospective study was an assessment of 114 men with prostate cancer who provided radical prostatectomy samples to the Australian Prostate Cancer Bioresource between 2006 and 2014. The prediction of CR was the primary outcome (median time to CR 79.8 months), and BCR was assessed as a secondary outcome (median time to BCR 41.7 months). The associations of (1) H&E ISUP grade groups and (2) modified ISUP grade groups informed by the Appl1, Sortilin and Syndecan-1 immunohistochemistry (IHC) labelling were modelled with BCR and CR using Cox proportional hazard approaches. IHC-assisted grading was more predictive than H&E for BCR (C-statistic 0.63 vs. 0.59) and CR (C-statistic 0.71 vs. 0.66). On adjusted analysis, IHC-assisted ISUP grading was independently associated with both outcome measures. IHC-assisted ISUP grading using the biomarker panel was an independent predictor of individual BCR and CR. Prospective studies are needed to further validate this biomarker technology and to define BCR and CR associations in real-world cohorts.

Low Risk of Hyperprogression with First-Line Chemoimmunotherapy for Advanced Non-Small Cell Lung Cancer: Pooled Analysis of 7 Clinical Trials.

BACKGROUND: Monotherapy immune checkpoint inhibitor (ICI) used in second- or later-line settings has been reported to induce hyperprogression. This study evaluated hyperprogression risk with ICI (atezolizumab) in the first-, second-, or later-line treatment of advanced non-small cell lung cancer (NSCLC), and provides insights into hyperprogression risk with contemporary first-line ICI treatment. METHODS: Hyperprogression was identified using Response Evaluation Criteria in Solid Tumours (RECIST)-based criteria in a dataset of pooled individual-participant level data from BIRCH, FIR, IMpower130, IMpower131, IMpower150, OAK, and POPLAR trials. Odds ratios were computed to compare hyperprogression risks between groups. Landmark Cox proportional-hazard regression was used to evaluate the association between hyperprogression and progression-free survival/overall survival. Secondarily, putative risk factors for hyperprogression among second- or later-line atezolizumab-treated patients were evaluated using univariate logistic regression models. RESULTS: Of the included 4644 patients, 119 of the atezolizumab-treated patients (n = 3129) experienced hyperprogression. Hyperprogression risk was markedly lower with first-line atezolizumab-either chemoimmunotherapy or monotherapy-compared to second/later-line atezolizumab monotherapy (0.7% vs. 8.8%, OR = 0.07, 95% CI, 0.04-0.13). Further, there was no statistically significant difference in hyperprogression risk with first-line atezolizumab-chemoimmunotherapy versus chemotherapy alone (0.6% vs. 1.0%, OR = 0.55, 95% CI, 0.22-1.36). Sensitivity analyses using an extended RECIST-based criteria including early death supported these findings. Hyperprogression was associated with worsened overall survival (HR = 3.4, 95% CI, 2.7-4.2, P < .001); elevated neutrophil-to-lymphocyte ratio was the strongest risk factor for hyperprogression (C-statistic = 0.62, P < .001). CONCLUSIONS: This study presents first evidence for a markedly lower hyperprogression risk in advanced NSCLC patients treated with first-line ICI, particularly with chemoimmunotherapy, as compared to second- or later-line ICI treatment.

Prognostic Associations of Concomitant Antibiotic Use in Patients with Advanced NSCLC Treated with Atezolizumab: Sensitivity Analysis of a Pooled Investigation of Five Randomised Control Trials.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been a significant milestone for the treatment of advanced non-small cell lung cancer (NSCLC). However, the efficacy of ICIs can vary substantially between patients, with disparities in treatment outcomes being potentially driving by changes in the microbiome. Antibiotics can cause dysbiosis and are hypothesised to impact the efficacy of ICIs Methods: Data were pooled from five randomised clinical control trials, IMpower130, IMpower131, IMpower150, OAK, and POPLAR, assessing atezolizumab in advanced NSCLC. Cox proportional hazard models were used to determine whether antibiotic use within 6-weeks before and after randomisation was associated with progression-free survival (PFS) and overall survival (OS) outcomes, with data further stratified by programmed death ligand-1 (PD-L1) status. RESULTS: Antibiotic use was significantly associated with worsened PFS (hazard ratio (HR) = 1.19 [1.08-1.30], p ≤ 0.001) and OS (HR = 1.27 [1.13-1.42], p ≤ 0.001) in patients treated with atezolizumab and those not treated with atezolizumab (PFS, HR = 1.21 [1.08-1.36] p < 0.001, OS, HR = 1.33 [1.16-1.51] p < 0.001). These associations were relatively consistent in both PD-L1 positive and PD-L1 negative. CONCLUSIONS: Antibiotic use within a ±6-week window was significantly associated with worse PFS and OS.