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Simple Summary: A novel biomarker panel (Appl1, Sortilin and Syndecan-1) was demonstrated as a strong independent predictor for both clinical and biochemical recurrence outcomes, with a higher prediction performance than traditional grading. This suggests that panel-derived patient reclassifications improve risk stratification. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

PURPOSE: The introduction of COVID-19 therapies containing ritonavir has markedly expanded the scope of use for this medicine. As a strong cytochrome P450 3A4 inhibitor, the use of ritonavir is associated with a high drug interaction risk. There are currently no data to inform clinician regarding the likely magnitude and duration of interaction between ritonavir-containing COVID-19 therapies and small-molecule kinase inhibitors (KIs) in patients with cancer. METHODS: Physiologically based pharmacokinetic modeling was used to conduct virtual clinical trials with a parallel group study design in the presence and absence of ritonavir (100 mg twice daily for 5 days). The magnitude and time course of changes in KI exposure when coadministered with ritonavir was evaluated as the primary outcome. RESULTS: Dosing of ritonavir resulted in a > 2-fold increase in steady-state area under the plasma concentration-time curve and maximal concentration for six of the 10 KIs. When the KI was coadministered with ritonavir, dose reductions to between 10% and 75% of the original dose were required to achieve an area under the plasma concentration-time curve within 1.25-fold of the value in the absence of ritonavir. CONCLUSION: To our knowledge, this study provides the first data to assist clinicians' understanding of the drug interaction risk associated with administering ritonavir-containing COVID-19 therapies to patients with cancer who are currently being treated with KIs. These data may support clinicians to make more informed dosing decisions for patients with cancer undergoing treatment with KIs who require treatment with ritonavir-containing COVID-19 antiviral therapies. These data may support clinicians to make more informed dosing decisions for patients with cancer undergoing treatment with kinase inhibitors who require treatment with ritonavir-containing COVID-19 antiviral therapies. [ABSTRACT FROM AUTHOR]

Neutropenia and diarrhoea are common and potentially serious adverse events associated with abemaciclib in advanced breast cancer (ABC), and the risk factors have been minimally explored. The study aimed to develop clinical prediction tools that allow personalized predictions of neutropenia and diarrhoea following abemaciclib initiation. Data was pooled from MONARCH 1, 2 and 3 trials investigating abemaciclib. Cox proportional hazard analysis was used to assess the association between pre-treatment clinicopathological data and grade ≥3 diarrhoea and neutropenia occurring within the first 365 days of abemaciclib use. Older age was associated with increased risk of grade ≥3 diarrhoea [HR [95%CI] for age > 70: 1.72 [1.14–2.58]; P = 0.009]. A clinical prediction tool for abemaciclib induced grade ≥3 neutropenia was optimally defined by race, ECOGPS and white blood cell count. Large discrimination between subgroups was observed; the highest risk subgroup had a 64% probability of grade ≥3 neutropenia within the first 365 days of abemaciclib (150 mg twice daily) + fulvestrant/NSAI, compared to 5% for the lowest risk subgroup. The study identified advanced age as significantly associated with an increased risk of abemaciclib induced grade ≥ 3 diarrhoea. A clinical prediction tool, defined by race, ECOGPS and pre-treatment white blood cell count, was able to discriminate subgroups with significantly different risks of grade ≥3 neutropenia following abemaciclib initiation. The tool may enable improved interpretation of personalized risks and the risk-benefit ratio of abemaciclib. • Neutropenia and diarrhoea are common adverse effects of abemaciclib. • Higher age was associated with abemaciclib induced diarrhoea. • White blood cell count, Race, and performance status were linked with neutropenia. • A prediction tool was developed to provide personalized risks of neutropenia. [ABSTRACT FROM AUTHOR]

Background: Abemaciclib is a CDK4/6 inhibitor used to treat hormone receptor–positive, human epidermal growth factor receptor 2–negative advanced breast cancer. The prognostic value of patient‐reported outcomes (PROs) has been minimally explored for treatment outcomes with CDK4/6 inhibitors. The performance of PROs compared with Eastern Cooperative Oncology Group performance status (ECOG‐PS) is unknown. Materials and Methods: This study pooled data from single‐arm trial, MONARCH 1, and randomized trials, MONARCH 2 and 3. In total, 900 patients initiated abemaciclib and 384 comparator therapy. Pretreatment PRO association with progression‐free survival (PFS) was modeled using Cox proportional hazards regression. Prediction performance was assessed via the C‐statistic (c). PROs were recorded via the European Organisation for Research and Treatment of Cancer QLQ‐C30. Results: Patient‐reported physical function, pain, role function, fatigue, and appetite loss were associated with PFS on univariable and adjusted analysis (p <.05). Physical function (c = 0.55) was most predictive, superior to ECOG‐PS (c = 0.54), with multivariable analysis indicating both provide independent information (p <.02). In the pooled randomized arms of MONARCH 2 and 3, the PFS treatment benefit (hazard ratio [95% confidence interval]) of abemaciclib (vs. comparators) was 0.75 (0.57–1.0) for low physical function, compared with 0.48 (0.40–0.59) for intermediate/high (p[interaction] =.01). Conclusion: PROs were identified as prognostic factors for PFS in patients initiating abemaciclib, with patient‐reported physical function containing independent predictive information beyond ECOG‐PS. Low physical function was associated with a decrease in the magnitude of PFS benefit from abemaciclib. PROs should be explored as prognostic, predictive, and stratification factors for clinical use and research trials of CDK4/6 inhibitors. Implications for Practice: For the first time, pretreatment patient‐reported outcomes have been shown to be independent prognostic markers for progression‐free survival (PFS) in patients diagnosed with hormone receptor–positive, human epidermal growth factor receptor 2–negative (HR+/HER2−) advanced breast cancer treated with abemaciclib. Importantly, patients with low physical function had a smaller PFS benefit from abemaciclib (vs. comparator) than patients with intermediate/high physical function. The present study demonstrates patient‐reported outcomes as a simple, effective, inexpensive, and independent prognostic marker for patients with HR+/HER2− advanced breast cancer treated with abemaciclib. Describing a cohort of patients with HR+/HER2− advanced breast cancer treated with abemaciclib, this article evaluates the prognostic association between pretreatment patient‐reported outcomes and progression‐free survival, the prediction performance of patient‐reported outcomes compared with ECOG performance status, and the effect of patient‐reported outcomes on the treatment benefit of abemaciclib versus comparator therapy. [ABSTRACT FROM AUTHOR]

Introduction. Afatinib is a first-line treatment option for patients with an advanced nonsmall cell lung cancer (NSCLC) expressing an epidermal growth factor receptor (EGFR) activating mutation. This study aimed to evaluate the association between early adverse events induced by afatinib and overall survival (OS) and progression free survival (PFS) in patients with advanced NSCLC. Methods. The study was a pooled post hoc analysis of the randomized trials LUX-Lung 3 and LUX-Lung 6 which evaluated afatinib versus pemetrexed-cisplatin or gemcitabine-cisplatin, respectively. Cox proportional hazard analysis was used to assess the impact of adverse events occurring within the first 28 days of afatinib therapy on the PFS and OS outcomes in treatment-naïve advanced NSCLC patients harbouring an EGFR activating mutation. Results. There were 468 patients who initiated first-line afatinib therapy within LUX-Lung 3 and LUX-Lung 6. A significant association between early rash and improved OS (hazard ratio (HR 95% CI); grade 1 = 0.74 [0.56–0.97]; grade 2+ = 0.64 [0.46–0.89]) (P = 0.018) was observed, although no significant association with PFS was present (P = 0.732). A significant association was identified between early diarrhoea and improved PFS (grade 1 = 0.83 [0.62–1.12]; grade 2+ = 0.62 [0.44–0.88]) (P = 0. 015), although no significant association with OS was present (P = 0.605). No associations between early stomatitis or paronychia and OS or PFS were identified. Conclusion. Rash occurring early after the initiation of afatinib was significantly associated with improved OS, an indicator that rash may be a surrogate of patients likely to achieve long-term survival. Consideration of using rash as a dose adjustment target may be warranted for future prospective trials aiming to optimise outcomes with afatinib therapy. [ABSTRACT FROM AUTHOR]

Background: HER2-positive advanced breast cancer (ABC) is associated with significant heterogeneity in long-term disease control and survival. Prognostic models for HER2-positive ABC patients considering first-line pertuzumab, trastuzumab, and docetaxel have not been evaluated. Methods: A pre-treatment prognostic model for progression-free survival (PFS) and overall survival (OS) was developed for HER2-positive ABC patients initiating first-line pertuzumab, trastuzumab, and docetaxel using clinicopathological data from the randomized clinical trial CLEOPATRA (n = 408). Cox proportional hazard analysis with a backwards deletion process was used. Results: Metastatic sites count (<3 vs. ≥ 3) and lactate dehydrogenase (LDH) (≤ ULN vs. >ULN) were identified as common pre-treatment risk predictors for PFS and OS (P < 0.05). Based on these two factors, patients can be characterized as one of three prognostic groups (good = 0 factors; intermediate = 1 factor; poor = 2 factors). The prognostic groups were associated with significantly different PFS (P < 0.001), with 3-year PFS probabilities of 44% (36–55), 28% (22–36), and 17% (11–29) for the good, intermediate and poor prognostic groups, respectively. Similarly, there was significant differences in OS (P < 0.001), with 4-year OS probabilities of 75% (95% CI: 67–84), 60% (53–68) and 31% (21–45) for the good, intermediate and poor prognostic groups, respectively. Conclusions: Pre-treatment prognostic groups identified for HER2-positive ABC patients initiating first-line pertuzumab, trastuzumab, and docetaxel had significantly different long-term disease control and survival outcomes. [ABSTRACT FROM AUTHOR]

Common therapies for HER2-positive advanced breast cancer (ABC) are associated with heterogeneity in prognosis and treatment benefit. Prognostic models of survival outcomes with ado-trastuzumab-emtansine (T-DM1) have not been evaluated. A pre-treatment prognostic model for overall survival (OS) and progression-free survival (PFS) based on clinicopathological factors was developed for HER2-positive ABC patients initiating second-line and later T-DM1 using data from the randomised clinical trials EMILIA and TH3RESA (n = 893). Pre-treatment prognostic groups were identified via recursive partitioning analysis. The most significant OS/PFS pre-treatment risk predictors were metastatic sites count (≤2 versus > 2) and ECOG performance-status (0 versus ≥ 1) (P < 0.05). Based on these two factors, patients can be characterised as one of three prognostic groups (good = 0 factors; intermediate = 1 factor; poor = 2 factors). The prognostic groups were identified as significantly associated with OS (P < 0.001) and PFS (P < 0.001). Median OS for the good, intermediate and poor prognostic groups were 40 (95%CI: 36–48), 25 (23–30) and 16 (14–19) months, respectively, and median PFS was 12 (10–15), 8 (7–9) and 6 (4–7) months. Pre-treatment prognostic groups with significant differences in OS and PFS for HER2-positive ABC patients initiating second-line and later T-DM1 were identified. For HER2-positive ABC patients considering initiating second-line and later T-DM1, the prognostic groups enable more personalized expectations of disease control, survival and absolute treatment benefit. • A prognostic tool for HER2-positive ABC patients initiating T-DM1 therapy. • Prognostic groups were significantly associated with PFS and OS. • Median PFS ranged from 6 to 12 months across the prognostic groups. • Median OS ranged from 16 to 40 months across the prognostic groups. • Provide personalized expectations of disease control and survival. [ABSTRACT FROM AUTHOR]

Axitinib is a second‐generation small‐molecule vascular endothelial growth factor receptor inhibitor. An axitinib steady‐state area under the plasma concentration–time curve (AUCSS) >300 ng/mL/hr is associated with superior progression‐free and overall survival. This study sought to characterize the physiological and molecular characteristics driving variability in axitinib AUCSS using physiologically based pharmacokinetic modeling to identify exposure biomarkers for this drug. The capacity to predict subjects likely to fail to achieve an axitinib AUCSS >300 ng/mL/hr was evaluated as a secondary outcome. A full physiologically based pharmacokinetic model incorporating mechanistic absorption was developed and verified for axitinib in accordance with the US Food and Drug Administration Guidance using Simcyp (Version 17.1). This model was used to simulate axitinib exposure over 7 days with twice‐daily dosing (5 mg) in a cohort of 1000 virtual cancer patients. Multiple linear regression modeling was used to identify patient characteristics associated with differences in axitinib exposure. A multivariable linear regression model incorporating hepatic cytochrome P450 (CYP) 3A4 abundance, albumin concentration, hepatic CYP1A2 abundance, hepatic CYP2C19 abundance, and intestinal CYP2C19 abundance provided robust prediction of axitinib AUCSS (R2 = 0.890; P <.001). By accounting for these variables, it was possible to identify subjects who would fail to achieve an effective axitinib AUCSS with a specificity of 88.7% and a sensitivity of 92.6%. Variability in axitinib AUCSS is primarily driven by differences in hepatic CYP3A4 abundance and albumin concentration. Consideration of these 2 characteristic is likely to be sufficient to individualize axitinib dosing. [ABSTRACT FROM AUTHOR]

Objective: Several predictors of survival have been identified in EGFR-positive non-small cell lung cancer (NSCLC) patients treated with first generation EGFR inhibitors. Prognostic models of survival outcomes with afatinib have not been evaluated. Methods: A prognostic tool for overall survival (OS)/progression free survival (PFS) based on pre-treatment clinicopathological factors was developed for EGFR-positive advanced NSCLC patients treated with first-line afatinib using penalised regression of individual-participant data from LUX-Lung 3 and 6 (n = 468). Favourable, intermediate and poor risk groups were identified and externally validated using LUX-Lung 1 (n = 390) and LUX-Lung 2 (n = 129) trials that initiated afatinib following previous chemotherapy or EGFR inhibitor treatment. Results: Discriminative performance was good in the development and validation cohorts. For patients treated with first-line afatinib, the median OS for the favourable, intermediate and poor risk groups were > 47.7, 29.3 and 16.4 months, respectively, and the median PFS were 17.3, 13.2 and 8.3 months, respectively. The improvement in median OS with afatinib use compared to chemotherapy was > 12.4 months for the favourable risk group, whereas no OS benefit was apparent for the poor risk group. The improvement in median PFS with afatinib use compared to chemotherapy was 10.2 months for the favourable risk group and 3.2 months for the poor risk group. Conclusions: A prognostic tool was developed and validated to identify favourable, intermediate and poor risk groups for OS/PFS in EGFR-positive advanced NSCLC patients treated with afatinib. The prognostic groups can inform the likely absolute OS/PFS benefit expected from afatinib compared to chemotherapy in first-line treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: The lung immune prognostic index (LIPI) is proposed as a simple risk scoring tool to differentiate differences in survival from immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (NSCLC). The tool has not been evaluated for performance in a NSCLC cohort initiating first-line, combination ICI approaches. In a large cohort of participants with chemotherapy-naïve, metastatic non-squamous NSCLC, we independently validated, for the first time, that LIPI discriminates a clear subgroup of patients likely to achieve reduced survival following the initiation of combination therapies including the ICI atezolizumab. The lung immune prognostic index (LIPI) is proposed to differentiate prognosis and treatment benefit from immune checkpoint inhibitors (ICIs) in advanced non-small cell lung cancer (NSCLC). There is minimal information on the predictive importance with first-line, combination ICI approaches. In post-hoc analysis of IMpower150, Cox-proportional hazard analysis assessed the association between LIPI groups and overall survival (OS)/progression free survival (PFS). IMpower150 involved chemotherapy-naïve, metastatic non-squamous NSCLC participants randomized atezolizumab-carboplatin-paclitaxel (ACP), bevacizumab-carboplatin-paclitaxel (BCP), or atezolizumab-BCP (ABCP). Good (0 factors), intermediate (1 factor), and poor LIPI (2 factors) were defined via derived neutrophil-to-lymphocyte ratio >3, and lactate dehydrogenase >upper limit of normal. Of 1148 participants, 548 had good, 479 intermediate, and 121 poor LIPI. In 385 participants randomised ABCP, a significant association between LIPI and OS (HR (95%CI): intermediate LIPI = 2.16 (1.47–3.18), poor LIPI = 5.28 (3.20–8.69), p < 0.001) and PFS (HR (95%CI): intermediate LIPI = 1.47 (1.11–1.95), poor LIPI = 3.02 (2.03–4.50), p < 0.001) was identified. Median OS was 24, 16, and 7 months for good, intermediate, and poor LIPI, respectively. ACP associations were similar. Relative OS treatment effect (HR 95%CI) of ABCP vs. BCP was 0.78 (0.53–1.15), 0.67 (0.49–0.91), and 0.87 (0.51–1.47) for the good, intermediate, and poor LIPI groups, respectively (P(interaction) = 0.66), with no benefit in median OS observed in the poor LIPI group. LIPI identified subgroups with significantly different survival following ABCP and ACP initiation for chemotherapy-naïve, metastatic non-squamous NSCLC. There was insufficient evidence that LIPI identifies patients unlikely to benefit from ABCP treatment. [ABSTRACT FROM AUTHOR]

• Treatment-specific clinical prediction models aim to reduce the uncertainty in therapeutic and adverse outcomes. • Models need to be of a clinical-grade with evidence of accuracy, reproducibility, generalizability, and user-friendliness. • The structured search identified seventeen treatment-specific clinical prediction models for therapeutic or adverse outcomes. • Significant gaps in the availability of validated models for both therapeutic and adverse outcomes were identified. Despite advances in the breast cancer treatment, significant variability in patient outcomes remain. This results in significant stress to patients and clinicians. Treatment-specific clinical prediction models allow patients to be matched against historical outcomes of patients with similar characteristics; thereby reducing uncertainty by providing personalised estimates of benefits, harms, and prognosis. To achieve this objective, models need to be clinical-grade with evidence of accuracy, reproducibility, generalizability, and be user-friendly. A structured search was undertaken to identify treatment-specific clinical prediction models for therapeutic or adverse outcomes in breast cancer using clinicopathological data. Significant gaps in the presence of validated models for available treatments was identified, along with gaps in prediction of therapeutic and adverse outcomes. Most models did not have user-friendly tools available. With the aim being to facilitate the selection of the best medicine for a specific patient and shared-decision making, future research will need to address these gaps. [ABSTRACT FROM AUTHOR]