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Richard Gelber

Publications and source records attributed to Richard Gelber.

9 recordsLinked to original sources
PubMed2026

Decluttering chemotherapy agents for HER2+early breast cancer: Do we still need carboplatin?

Over the past two decades, targeted anti-HER2 therapies have transformed management of HER2-positive early breast cancer (HER2 + eBC), enabling chemotherapy de-escalation without compromising efficacy. This review assesses the rationale for incorporating carboplatin into (neo)adjuvant regimens and critically examines its routine use in unselected patient populations with HER2-positive eBC. While initial translational and early clinical studies suggested that adding carboplatin to taxane-based chemotherapy combined with anti-HER2 therapy might be beneficial, more recent randomized trials have failed to demonstrate incremental advantage and have raised concerns about increased toxicity. Emerging prognostic and predictive biomarkers, most notably the HER2DX genomic assay, hold promise for identifying high-risk patient subgroups who may derive meaningful benefit from carboplatin. We conclude that carboplatin should not be routinely added in unselected HER2-positive early breast cancer, but rather, a biomarker-driven, personalized strategy is recommended to enhance patient selection, refine the treatment algorithm, and maximize the cost-to-benefit ratio.

De-escalating neoadjuvant treatments↗
PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74&#xb7;1 months (IQR 68&#xb7;3-75&#xb7;4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0&#xb7;84 [95% CI 0&#xb7;79-0&#xb7;88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11&#xb7;6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0&#xb7;41-0&#xb7;93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0&#xb7;36-0&#xb7;48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (&#x2265;70&#xb7;0%; mean absolute improvement 12&#xb7;1 percentage points [SD 2&#xb7;8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0&#xb7;010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans↗
PubMed2006

Estimation in regression models for longitudinal binary data with outcome-dependent follow-up.

In many observational studies, individuals are measured repeatedly over time, although not necessarily at a set of pre-specified occasions. Instead, individuals may be measured at irregular intervals, with those having a history of poorer health outcomes being measured with somewhat greater frequency and regularity. In this paper, we consider likelihood-based estimation of the regression parameters in marginal models for longitudinal binary data when the follow-up times are not fixed by design, but can depend on previous outcomes. In particular, we consider assumptions regarding the follow-up time process that result in the likelihood function separating into two components: one for the follow-up time process, the other for the outcome measurement process. The practical implication of this separation is that the follow-up time process can be ignored when making likelihood-based inferences about the marginal regression model parameters. That is, maximum likelihood (ML) estimation of the regression parameters relating the probability of success at a given time to covariates does not require that a model for the distribution of follow-up times be specified. However, to obtain consistent parameter estimates, the multinomial distribution for the vector of repeated binary outcomes must be correctly specified. In general, ML estimation requires specification of all higher-order moments and the likelihood for a marginal model can be intractable except in cases where the number of repeated measurements is relatively small. To circumvent these difficulties, we propose a pseudolikelihood for estimation of the marginal model parameters. The pseudolikelihood uses a linear approximation for the conditional distribution of the response at any occasion, given the history of previous responses. The appeal of this approximation is that the conditional distributions are functions of the first two moments of the binary responses only. When the follow-up times depend only on the previous outcome, the pseudolikelihood requires correct specification of the conditional distribution of the current outcome given the outcome at the previous occasion only. Results from a simulation study and a study of asymptotic bias are presented. Finally, we illustrate the main results using data from a longitudinal observational study that explored the cardiotoxic effects of doxorubicin chemotherapy for the treatment of acute lymphoblastic leukemia in children.

Adolescent↗
PubMed2004

American Society of Clinical Oncology technology assessment on the use of aromatase inhibitors as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer: status report 2004.

PURPOSE: To update the 2003 American Society of Clinical Oncology technology assessment on adjuvant use of aromatase inhibitors. RECOMMENDATIONS: Based on results from multiple large randomized trials, adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer should include an aromatase inhibitor in order to lower the risk of tumor recurrence. Neither the optimal timing nor duration of aromatase inhibitor therapy is established. Aromatase inhibitors are appropriate as initial treatment for women with contraindications to tamoxifen. For all other postmenopausal women, treatment options include 5 years of aromatase inhibitors treatment or sequential therapy consisting of tamoxifen (for either 2 to 3 years or 5 years) followed by aromatase inhibitors for 2 to 3, or 5 years. Patients intolerant of aromatase inhibitors should receive tamoxifen. There are no data on the use of tamoxifen after an aromatase inhibitor in the adjuvant setting. Women with hormone receptor-negative tumors should not receive adjuvant endocrine therapy. The role of other biomarkers such as progesterone receptor and HER2 status in selecting optimal endocrine therapy remains controversial. Aromatase inhibitors are contraindicated in premenopausal women; there are limited data concerning their role in women with treatment-related amenorrhea. The side effect profiles of tamoxifen and aromatase inhibitors differ. The late consequences of aromatase inhibitor therapy, including osteoporosis, are not well characterized. CONCLUSION: The Panel believes that optimal adjuvant hormonal therapy for a postmenopausal woman with receptor-positive breast cancer includes an aromatase inhibitor as initial therapy or after treatment with tamoxifen. Women with breast cancer and their physicians must weigh the risks and benefits of all therapeutic options.

Aged↗
PubMed2004

Toremifene and tamoxifen are equally effective for early-stage breast cancer: first results of International Breast Cancer Study Group Trials 12-93 and 14-93.

BACKGROUND: Toremifene is a chlorinated derivative of tamoxifen, developed to improve its risk-benefit profile. The International Breast Cancer Study Group (IBCSG) conducted two complementary randomized trials for peri- and postmenopausal patients with node-positive breast cancer to compare toremifene versus tamoxifen as the endocrine agent and simultaneously investigate a chemotherapy-oriented question. This is the first report of the endocrine comparison after a median follow-up of 5.5 years. PATIENTS AND METHODS: 1035 patients were available for analysis: 75% had estrogen receptor (ER)-positive primary tumors, the median number of involved axillary lymph nodes was three and 81% received prior adjuvant chemotherapy. RESULTS: Toremifene and tamoxifen yielded similar disease-free (DFS) and overall survival (OS): 5-year DFS rates of 72% and 69%, respectively [risk ratio (RR)=0.95; 95% confidence interval (CI)=0.76-1.18]; 5-year OS rates of 85% and 81%, respectively (RR = 1.03; 95% CI = 0.78-1.36). Similar outcomes were observed in the ER-positive cohort. Toxicities were similar in the two treatment groups with very few women (<1%) experiencing severe thromboembolic or cerebrovascular complications. Quality of life results were also similar. Nine patients developed early stage endometrial cancer (toremifene, six; tamoxifen, three). CONCLUSIONS: Toremifene is a valid and safe alternative to tamoxifen in postmenopausal women with endocrine-responsive breast cancer.

Aged↗
PubMed2002

Concentrations of protease inhibitors in cord blood after in utero exposure.

OBJECTIVE: To determine the concentrations of protease inhibitors in cord blood after prenatal protease inhibitor use by pregnant women. DESIGN: Retrospective analysis of samples collected in a clinical trial. METHODS: Protease inhibitor concentrations were measured in cord blood samples collected from women enrolling in the PACTG 316 study who were receiving prenatal protease inhibitor antiretroviral therapy. RESULTS: In cord blood samples from 68 women treated with protease inhibitors during pregnancy, the concentration of these drugs was below the assay lower limit of detection in most samples, including all samples from women receiving indinavir (n = 21) and saquinavir (n = 8), 5 of 6 samples (83%) from women receiving ritonavir and 24 of 38 samples (63%) from women receiving nelfinavir. CONCLUSIONS: Low protease inhibitor concentrations in the fetus decrease the likelihood of teratogenic and toxic effects of these drugs but could fail to provide protection from transplacental or intrapartum transmission of HIV-1.

Adult↗
PubMed2002

Parameter estimation in longitudinal studies with outcome-dependent follow-up.

In many observational studies, individuals are measured repeatedly over time, although not necessarily at a set of prespecified occasions. Instead, individuals may be measured at irregular intervals, with those having a history of poorer health outcomes being measured with somewhat greater frequency and regularity; i.e., those individuals with poorer health outcomes may have more frequent follow-up measurements and the intervals between their repeated measurements may be shorter. In this article, we consider estimation of regression parameters in models for longitudinal data where the follow-up times are not fixed by design but can depend on previous outcomes. In particular, we focus on general linear models for longitudinal data where the repeated measures are assumed to have a multivariate Gaussian distribution. We consider assumptions regarding the follow-up time process that result in the likelihood function separating into two components: one for the follow-up time process, the other for the outcome process. The practical implication of this separation is that the former process can be ignored when making likelihood-based inferences about the latter; i.e., maximum likelihood (ML) estimation of the regression parameters relating the mean of the longitudinal outcomes to covariates does not require that a model for the distribution of follow-up times be specified. As a result, standard statistical software, e.g., SAS PROC MIXED (Littell et al., 1996, SAS System for Mixed Models), can be used to analyze the data. However, we also demonstrate that misspecification of the model for the covariance among the repeated measures will, in general, result in regression parameter estimates that are biased. Furthermore, results of a simulation study indicate that the potential bias due to misspecification of the covariance can be quite considerable in this setting. Finally, we illustrate these results using data from a longitudinal observational study (Lipshultz et al., 1995, New England Journal of Medicine 332, 1738-1743) that explored the cardiotoxic effects of doxorubicin chemotherapy for the treatment of acute lymphoblastic leukemia in children.

Adolescent↗