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Strain energy is a fundamental measure of the steric and configurational properties of organic molecules. The ability to estimate strain energy through quantum chemical simulations requires at minimum the knowledge of an initial set of nuclear coordinates. In general, such knowledge is not categorically known when screening or generating large numbers of molecule candidates in the context of molecular design. We present a machine learning approach to predict hydrocarbon strain energies using Benson group equivalents. A featurization strategy is crafted by concatenating the molecule group equivalent counts with easily computable molecular fingerprints. The data are obtained from electronic structure calculations we performed on a set of 166 previously synthesized strained hydrocarbons. These data are provided and include gas phase enthalpies of formation and associated optimized atomic coordinates. The strain energy prediction accuracy of several statistical learning methods is evaluated, and their respective merits and limitations are discussed.

Predictive models for the performance of explosives and propellants are important for their design, optimization, and safety. Thermochemical codes can predict some of these properties from fundamental quantities such as density and formation energies that can be obtained from first principles. Models that are simpler to evaluate are desirable for efficient, rapid screening of material screening. In addition, interpretable models can provide insight into the physics and chemistry of these materials that could be useful to direct new synthesis. Current state-of-the-art performance models are based on either the parametrization of physics-based expressions or data-driven approaches with minimal interpretability. We use parsimonious neural networks (PNNs) to discover interpretable models for the specific impulse of propellants and detonation velocity and pressure for explosives using data collected from the open literature. A combination of evolutionary optimization with custom neural networks explores and trains models with objective functions that balance accuracy and complexity. For all three properties of interest, we find interpretable models that are Pareto optimal in the accuracy and simplicity space.

For many experimentally measured chemical properties that cannot be directly computed from first-principles, the existing physics-based models do not extrapolate well to out-of-sample molecules, and experimental datasets themselves are too small for traditional machine learning (ML) approaches. To overcome these limitations, we apply a transfer learning approach, whereby we simultaneously train a multi-target regression model on a small number of molecules with experimentally measured values and a large number of molecules with related computed properties. We demonstrate this methodology on predicting the experimentally measured impact sensitivity of energetic crystals, finding that both characteristics of the computed dataset and model architecture are important to prediction accuracy of the small experimental dataset. Our directed-message passing neural network (D-MPNN) ML model using transfer learning outperforms direct-ML and physics-based models on a diverse test set, and the new methods described here are widely applicable to modeling many other structure-property relationships.

Deep learning has shown great potential for generating molecules with desired properties. But the cost and time required to obtain relevant property data have limited study to only a few classes of materials for which extensive data have already been collected. We develop a deep learning method that combines a generative model with a property prediction model to fuse small data of one class of molecules with larger data in another class. Common low-level physicochemical properties are jointly embedded into a latent space that can be used to design molecules in the smaller class. The chemical space around the molecules in the training set is explored through local gradient ascent optimization. Based on nine molecules from the original training set, nine new molecules are found to have improved properties while remaining structurally similar to the training molecules thereby easing requirements for entirely new synthesis routes. Validation is performed using an equilibrium thermochemistry code to verify the molecules and target properties. A specific example targeting the Chapman-Jouguet velocity and small data for nitrogen-rich molecules is shown. Despite the relative lack of nitrogen-rich molecule data, the results demonstrate that fusing and joint embedding with plentiful low nitrogen molecular data can produce higher generative performance than using the scarce data alone., (© 2021 Wiley-VCH GmbH.)

A priori knowledge of physicochemical properties such as melting and boiling could expedite materials discovery. However, theoretical modeling from first principles poses a challenge for efficient virtual screening of potential candidates. As an alternative, the tools of data science are becoming increasingly important for exploring chemical datasets and predicting material properties. Herein, we extend a molecular representation, or set of descriptors, first developed for quantitative structure-property relationship modeling by Yalkowsky and coworkers known as the Unified Physicochemical Property Estimation Relationships (UPPER). This molecular representation has group-constitutive and geometrical descriptors that map to enthalpy and entropy; two thermodynamic quantities that drive thermal phase transitions. We extend the UPPER representation to include additional information about sp 2 -bonded fragments. Additionally, instead of using the UPPER descriptors in a series of thermodynamically-inspired calculations, as per Yalkowsky, we use the descriptors to construct a vector representation for use with machine learning techniques. The concise and easy-to-compute representation, combined with a gradient-boosting decision tree model, provides an appealing framework for predicting experimental transition temperatures in a diverse chemical space. An application to energetic materials shows that the method is predictive, despite a relatively modest energetics reference dataset. We also report competitive results on diverse public datasets of melting points (i.e., OCHEM, Enamine, Bradley, and Bergström) comprised of over 47k structures. Open source software is available at https://github.com/USArmyResearchLab/ARL-UPPER., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)

We develop a convolutional neural network capable of directly parsing the 3D electronic structure of a molecule described by spatial point data for charge density and electrostatic potential represented as a 4D tensor. This method effectively bypasses the need to construct complex representations, or descriptors, of a molecule. This is beneficial because the accuracy of a machine learned model depends on the input representation. Ideally, input descriptors encode the essential physics and chemistry that influence the target property. Thousands of molecular descriptors have been proposed, and proper selection of features requires considerable domain expertise or exhaustive and careful statistical downselection. In contrast, deep learning networks are capable of learning rich data representations. This provides a compelling motivation to use deep learning networks to learn molecular structure-property relations from "raw" data. The convolutional neural network model is jointly trained on over 20,000 molecules that are potentially energetic materials (explosives) to predict dipole moment, total electronic energy, Chapman-Jouguet (C-J) detonation velocity, C-J pressure, C-J temperature, crystal density, HOMO-LUMO gap, and solid phase heat of formation. This work demonstrates the first use of complete 3D electronic structure for machine learning of molecular properties.

This work presents efforts to augment the performance of data-driven machine learning algorithms for reaction template recommendation used in computer-aided synthesis planning software. Often, machine learning models designed to perform the task of prioritizing reaction templates or molecular transformations are focused on reporting high-accuracy metrics for the one-to-one mapping of product molecules in reaction databases to the template extracted from the recorded reaction. The available templates that get selected for inclusion in these machine learning models have been previously limited to those that appear frequently in the reaction databases and exclude potentially useful transformations. By augmenting open-access data sets of organic reactions with explicitly calculated template applicability and pretraining a template-relevance neural network on this augmented applicability data set, we report an increase in the template applicability recall and an increase in the diversity of predicted precursors. The augmentation and pretraining effectively teaches the neural network an increased set of templates that could theoretically lead to successful reactions for a given target. Even on a small data set of well-curated reactions, the data augmentation and pretraining methods resulted in an increase in top-1 accuracy, especially for rare templates, indicating that these strategies can be very useful for small data sets.

Background: Pediatric trauma patients with cervical spine (CS) immobilization using a cervical collar often require procedural sedation (PS) for radiologic imaging. The limited ability to perform airway maneuvers while CS immobilized with a cervical collar is a concern for emergency department (ED) staff providing PS., Objective: To describe the use of PS and analgesia for radiologic imaging acquisition in pediatric trauma patients with CS immobilization., Methods: Retrospective medical record review of all trauma patients with CS immobilization at a high-volume pediatric trauma center was performed. Patient demographics, imaging modality, PS success, sedative and analgesia medications, and adverse events were analyzed. Patients intubated prior to arrival to the ED were excluded., Results: A total of 1417 patients with 1898 imaging encounters met our inclusion criteria. A total of 398 patients required more than one radiographic imaging procedure. The median age was 8 years (range 3.8-12.75 years). Computed tomography of the head was used in 974 of the 1898 patients (51.3%). A total of 956 of the 1898 patients (50.4%) required sedatives or analgesics for their radiographic imaging, with 875 (91.5%) requiring a single sedative or analgesic agent, and 81 (8.5%) requiring more than one medication. Airway obstruction was the most common adverse event, occurring in 5 of 956 patients (0.3%). All imaging procedures were successfully completed., Conclusion: Only 50% of CS immobilized, nonintubated patients required a single sedative or analgesic medication for their radiologic imaging. Procedural success was high, with few adverse events., (Copyright © 2019 Elsevier Inc. All rights reserved.)

We describe the development of a density-dependent transferable coarse-grain model of crystalline hexahydro-1,3,5-trinitro-s-triazine (RDX) that can be used with the energy conserving dissipative particle dynamics method. The model is an extension of a recently reported one-site model of RDX that was developed by using a force-matching method. The density-dependent forces in that original model are provided through an interpolation scheme that poorly conserves energy. The development of the new model presented in this work first involved a multi-objective procedure to improve the structural and thermodynamic properties of the previous model, followed by the inclusion of the density dependency via a conservative form of the force field that conserves energy. The new model accurately predicts the density, structure, pressure-volume isotherm, bulk modulus, and elastic constants of the RDX crystal at ambient pressure and exhibits transferability to a liquid phase at melt conditions.

Clathrate hydrates are solid crystalline structures most commonly formed from solutions that have nucleated to form a mixed solid composed of water and gas. Understanding the mechanism of clathrate hydrate nucleation is essential to grasp the fundamental chemistry of these complex structures and their applications. Molecular dynamics (MD) simulation is an ideal method to study nucleation at the molecular level because the size of the critical nucleus and formation rate occur on the nano scale. Various analysis methods for nucleation have been developed through MD to analyze nucleation. In particular, the mean first-passage time (MFPT) and survival probability (SP) methods have proven to be effective in procuring the nucleation rate and critical nucleus size for monatomic systems. This study assesses the MFPT and SP methods, previously used for monatomic systems, when applied to analyzing clathrate hydrate nucleation. Because clathrate hydrate nucleation is relatively difficult to observe in MD simulations (due to its high free energy barrier), these methods have yet to be applied to clathrate hydrate systems. In this study, we have analyzed the nucleation rate and critical nucleus size of methane hydrate using MFPT and SP methods from data generated by MD simulations at 255 K and 50 MPa. MFPT was modified for clathrate hydrate from the original version by adding the maximum likelihood estimate and growth effect term. The nucleation rates calculated by MFPT and SP methods are within 5%, and the critical nucleus size estimated by the MFPT method was 50% higher, than values obtained through other more rigorous but computationally expensive estimates. These methods can also be extended to the analysis of other clathrate hydrates.

Nucleation from solution is a ubiquitous phenomenon with relevance to myriad scientific disciplines, including pharmaceuticals, biomineralization, and disease. One prominent example is the nucleation of clathrate hydrates, multicomponent crystalline inclusion compounds relevant to the energy industry where they block pipelines and also constitute a potential vast energy resource. Despite their importance, the molecular mechanism of incipient hydrate formation remains unknown. Herein, we employ advanced molecular simulation tools (pB histogram, equilibrium path sampling) to provide a statistical-mechanical basis for extracting physical insight into the molecular steps by which clathrates form. Through testing the Mutually Coordinated Guest (MCG) order parameter, we demonstrate that both guest (methane) and host (water) structuring are crucial to accurately describe the nucleation of hydrates and determine a critical nucleus size of MCG-1 = 16 at 255 K and 500 bar. Equipped with a validated (and novel) reaction coordinate, subsequent equilibrium path sampling simulations yield the free energy barrier and nucleation rate. The resulting quantitative nucleation process is described by the MCG clustering mechanism. This constitutes a significant advance in the field of hydrates research, as the fitness of a molecular descriptor has never been statistically verified. More broadly, this work has significance to a wide range of multicomponent nucleation contexts wherein the formation mechanism depends on contributions from both solute and solvent.

The current knowledge and description of guest molecules within clathrate hydrates only accounts for occupancy within regular polyhedral water cages. Experimental measurements and simulations, examining the tert-butylamine + H2 + H2O hydrate system, now suggest that H2 can also be incorporated within hydrate crystal structures by occupying interstitial sites, that is, locations other than the interior of regular polyhedral water cages. Specifically, H2 is found within the shared heptagonal faces of the large (4(3)5(9)6(2)7(3)) cage and in cavities formed from the disruption of smaller (4(4)5(4)) water cages. The ability of H2 to occupy these interstitial sites and fluctuate position in the crystal lattice demonstrates the dynamic behavior of H2 in solids and reveals new insight into guest-guest and guest-host interactions in clathrate hydrates, with potential implications in increasing overall energy storage properties., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Methane clathrate hydrate nucleation and growth is investigated via analysis of molecular dynamics simulations using a new order parameter. This order parameter (OP), named the Mutually Coordinated Guest (MCG) OP, quantifies the appearance and connectivity of molecular clusters composed of guests separated by water clusters. It is the first two-component OP used for quantifying hydrate nucleation and growth. The algorithm for calculating the MCG OP is described in detail. Its physical motivation and advantages compared to existing methods are discussed.

To better understand the self-assembly of small molecules and nanoparticles adsorbed at interfaces, we have performed extensive Monte Carlo simulations of a simple lattice model based on the seven hard "tetrominoes", connected shapes that occupy four lattice sites. The equations of state of the pure fluids and all of the binary mixtures are determined over a wide range of density, and a large selection of multicomponent mixtures are also studied at selected conditions. Calculations are performed in the grand canonical ensemble and are analogous to real systems in which molecules or nanoparticles reversibly adsorb to a surface or interface from a bulk reservoir. The model studied is athermal; objects in these simulations avoid overlap but otherwise do not interact. As a result, all of the behavior observed is entropically driven. The one-component fluids all exhibit marked self-ordering tendencies at higher densities, with quite complex structures formed in some cases. Significant clustering of objects with the same rotational state (orientation) is also observed in some of the pure fluids. In all of the binary mixtures, the two species are fully miscible at large scales, but exhibit strong species-specific clustering (segregation) at small scales. This behavior persists in multicomponent mixtures; even in seven-component mixtures of all the shapes there is significant association between objects of the same shape. To better understand these phenomena, we calculate the second virial coefficients of the tetrominoes and related quantities, extract thermodynamic volume of mixing data from the simulations of binary mixtures, and determine Henry's law solubilities for each shape in a variety of solvents. The overall picture obtained is one in which complementarity of both the shapes of individual objects and the characteristic structures of different fluids are important in determining the overall behavior of a fluid of a given composition, with sometimes counterintuitive results. Finally, we note that no sharp phase transitions are observed but that this appears to be due to the small size of the objects considered. It is likely that complex phase behavior may be found in systems of larger polyominoes.

The use of evolutionary strategy optimizations in fitting empirical potentials against first-principles data is considered. Empirical potentials can involve a large number of interdependent quantities, the number varying with the complexity of the potential, and the optimization of these presents a challenging numerical problem. Evolutionary strategies are a general class of optimization methods that mimic natural selection by stochastically evolving a population of trial solutions according to rules that select for high values of some fitness function. In this work we apply a variety of evolutionary optimization methods to a representative "parametrization problem" in order to determine which such methods are well-suited to such applications. Prior work on the design of evolutionary strategies has generally focused on finding the extrema of relatively simple mathematical functions, and the findings of such studies may not be transferable to chemical applications of very high dimensionality. The test problem consists of parametrization of the Feuston-Garofalini all-atom potential developed for simulation of silicic acid oligomerization in aqueous solution (Feuston, B. P.; Garofalini, S. H. J. Phys. Chem. 1990, 94, 5351). "Meta-optimization" of the evolutionary method is first considered by fitting this potential against itself, using a wide variety of population sizes, recombination algorithms, mutation-size control methods, and selection methods. Simulated annealing is also considered as an alternative approach. Optimal choices of population size, recombination operator, mutation size control approach, and selection method are discussed, as well as the quantity of data required for the parametrization. It is clear from comparisons of multiple independent optimizations that, even when fitting this potential against itself, there are a considerable number of local extrema in the fitness function. Evolutionary methods are found to be competitive with simulated annealing and are more easily parallelized. Finally, the potential is reparametrized against reference data taken from a Car-Parrinello Molecular Dynamics trajectory of several relevant silicate species in aqueous solution, again using several variant algorithms.

Background: Multiple trials have been performed to evaluate second-line clinical chemotherapy in patients with advanced nonsmall cell lung carcinoma (NSCLC). However, no single agent or combination has demonstrated superior activity., Methods: Patients with advanced NSCLC who had already received one chemotherapeutic regimen were treated with topotecan (0.75 mg/m(2) over 30 minutes, Days 1-5) and gemcitabine (400 mg/m(2) over 30 minutes, Days 1 and 5) every 21 days., Results: Of 35 patients who were treated, 4 (11%) achieved a partial responses and 8 (23%) hadstable disease for at least four courses of treatment. The response rate for patients with refractory disease (progressing during frontline chemotherapy) was 18% (3 of 17) with 18% having stable disease for at least four courses of treatment. The median survival of the entire group was 7 months (range, 1.5-44 months) and 20% (7 of 35) of patients were alive 1 year from the initiation of topotecan and gemcitabine treatment. Patients with refractory disease had a median survival of 4(1/2) months, with 6-month and 1-year survival rates of 47% and 18%, respectively. During Course 1, five patients (14%) developed Grade IV neutropenia and three patients (9%) developed Grade IV thrombocytopenia. Nonhematologic toxicity was relatively mild, with one patient developing Grade III side effects (fatigue) and eight patients (23%) developing Grade II nonhematologic side effects., Conclusions: The combination of topotecan and gemcitabine demonstrated antitumor activity with a modest side effect profile in patients with advanced, previously treated NSCLC., (Copyright 2002 American Cancer Society.)

A unique feature of soccer is the purposeful use of the head for controlling, passing, and shooting a soccer ball. Some concern has been expressed in the literature on the cumulative effects of heading on soccer players. Certain neurophysiologic and neuropsychologic changes have been reported in current or retired players, with heading being blamed. A major factor that could influence some of the findings is a player's history of concussive episodes, which are known to influence brain function. These episodes can occur during aspects of the game other than heading. We interviewed all male and female soccer players (N = 137, average age = 20.5 years) who competed at the U.S. Olympic Sports Festival in 1993. The mechanisms of injuries, frequency, and sequelae were determined. There were 74 concussions in 39 male players (grade I = 50) and 28 concussions in 23 female players (grade I = 19). For the men, 48 of the 74 episodes were from collisions with another player. For the women, 20 of 28 were from such collisions. Headaches, being "dazed," and dizziness were the most common symptoms reported. Based on concussion history, the odds are 50% that a man, and 22% that a woman, will sustain a concussion within a 10-year period. The data indicate that concussions from player-to-player contact are a frequent hazard in soccer. Head injuries incurred this way may be more of an influence for published findings of physiologic and psychologic deficiencies than routine heading of the soccer ball.

Clinicians are increasingly aware that mechanical aspects of foot deformities, such as Charcot changes, clawtoes, bunion deformities, or cavus or planus foot deformities, might have an impact on the occurrence, potential healing, and recurrence of foot ulcers. We report the prevalence of plain radiographic changes and attempt to rate the severity of those deformities in the feet of 456 diabetic veteran medicine clinic enrollees. All 456 radiographs were reviewed by orthopaedic surgeons to specifically identify Charcot changes, presence of arterial calcification, dislocation of the lesser toe metatarsophalangeal joints, hallux interphalangeal joint dislocation, and radiographic evidence of previous surgery. Radiographs of 428 patients were taken while weight-bearing, and these were reviewed to quantify hallux valgus angles, intermetatarsal 1-2 angles, fifth metatarsal-proximal phalangeal angles, second metatarsal lengths, lateral talocalcaneal and talar-first metatarsal angles, and claw toe deformities. The prevalence of Charcot changes was 1.4% (six subjects), and all had radiographic evidence of midfoot Charcot changes. Other deformities, such as clawtoes, hallux valgus, lesser toe joint dislocations, and alterations in arch height, are more common in veterans with diabetes.

We performed a prospective study of the results of treatment of primary cutaneous melanoma of the foot in 282 patients to determine if there were any factors that could predict survival. These patients were part of a group of 1018 patients who had primary cutaneous melanoma affecting the lower extremity. We found that 184 (65 per cent) of the 282 patients had a tumor that extended into the reticular dermis or subcutaneous tissue (a Level-IV or V lesion according to the system of Clark et al.). Sixty-three patients (22 per cent) had evidence of local, regional, or distant metastatic disease at the time of presentation. Location of the melanoma on the plantar aspect of the foot was found to be an independent variable that was associated with a poorer rate of survival (56 per cent at five years and 46 per cent at ten years) compared with a dorsally located melanoma (80 per cent at five years and 67 per cent at ten years). Subungual lesions were associated with an extremely low rate of survival (17 per cent at ten years); however, because of the small number of subungual lesions that were followed, the difference in survival between the patients who had a plantar lesion and those who had a subungual lesion was not significant (p = 0.52). Variables, in order of decreasing importance, that had independent prognostic significance for survival of patients who had a melanoma of the foot were the clinical stage of the lesion at the time of presentation (p < 0.001) and the age of the patient (p < 0.03), as determined by multivariate analysis.(ABSTRACT TRUNCATED AT 250 WORDS)

Thirty-seven uncemented primary porous coated anatomic (PCA) total hip arthroplasties (THA) that were performed in 33 patients for the diagnosis of avascular necrosis (AVN) between June 1984 and December 1986 were reexamined at four- to six-year follow-up periods. Final clinical evaluation showed an 86-point average Harris hip rating (range, 47-100 points), which had improved from an average preoperative rating of 42 points (range, 20-61 points). Thigh pain, which was usually not functionally limiting, occurred in 11 patients (25%), and seven patients (16%) had a moderate or severe limp. Nine patients (20%) required the use of a cane. Long-term radiographic evaluation in 37 hips demonstrated acetabular cup migration in one hip, acetabular lucencies in four hips (11%), and acetabular bead loosening in ten hips (27%). Femoral subsidence occurred in five hips (14%) and femoral bead loosening in 11 hips (30%). Thirty hips (81%) demonstrated radiographic evidence of stable bony ingrowth. No revisions were performed for aseptic loosening, but two prostheses were removed for infection. These results of uncemented THA in patients with AVN appear to be as good or better than the results reported for cemented arthroplasty in AVN at this interval of a follow-up period. This study supports the use of uncemented devices, especially with the newer designs and increasing surgical experience in this difficult patient population.

Seventy-five evaluable patients with metastatic breast cancer refractory to frontline chemotherapy were treated with vinblastine 1.5 mg/m2 by continuous intravenous infusion for five days, intravenous infusion of methotrexate 200 mg/m2, and appropriate calcium leukovorin rescue. Thirty-eight patients were treated with vinblastine followed by methotrexate and calcium leukovorin, while 37 patients were treated with these same drugs in reverse sequence. In 17 patients (23%) an objective remission was achieved, while 39 remained stable for a period in excess of eight weeks. The median duration of remission was two months, and the median duration of survival was six months. The two regimens were well balanced for commonly used pretreatment prognostic factors. There was no difference in response rate and duration of response between the two treatment regimens. In patients with no prior exposure to methotrexate, the remission rate was 37% (11 of 30) compared with 13% (6 of 45). The treatment was well tolerated, and the dose-limiting toxicity was myelosuppression. This combination of drugs is effective in patients who have not been exposed to either drug, while it is only marginally effective in patients previously treated with methotrexate or vinblastine.

We have investigated the efficacy of intravenous antibiotic therapy as a prophylactic measure to prevent infection following low-velocity gunshot fractures. Ninety-six consecutive patients were randomized prospectively to either an antibiotic group (Group I) or a nonantibiotic group (Group II) and were followed in a special gunshot wound clinic. Only patients with fractures that could be treated by closed techniques and did not require internal fixation were included. Sixty-seven patients (73 fractures) were followed radiographically. At follow-up, 36 fractures in Group 1 and 37 fractures in Group II comprised the study group. A total of two infections, one in each group, was documented. No significant infection prophylaxis was demonstrated by the use of intravenous antibiotics in these injuries.

Between May 1977 and April 1980, 238 patients with operable breast cancer were treated with adjuvant fluorouracil, doxorubicin, and cyclophosphamide (FAC) chemotherapy. All patients were randomized to receive FAC alone or FAC with nonspecific immunotherapy with Bacillus Calmette-Guerin (BCG) vaccine. A randomization for routine postoperative irradiation was included in the study in May 1978. At the median follow-up of 33 months, 53 patients had developed recurrent disease. Up to the present time, there have been no significant differences in the disease-free survival of patients treated with FAC alone from those treated with FAC + BCG (P = 0.21). The disease-free survival for patients treated with and without routine postoperative irradiation was similar (P = 0.99). Disease-free survival of premenopausal and postmenopausal women was similar. The overall estimate of disease-free survival was 72% at 3 years.

Peptichemio is a polypeptide complex of L-phenylalanine mustard. Because of structural similarities between melphalan (L-PAM) and Peptichemio a prospective randomized study was done to compare the therapeutic efficacy of these two agents. After failing various combinations of doxorubicin, cyclophosphamide, fluorouracil, methotrexate, and vincristine patients with advanced breast cancer were randomized to receive either Peptichemio or L-PAM. Peptichemio was administered at 75-100 mg/m2 and L-PAM at 30-40 mg/m2 IV q 3-4 week interval. Of 56 evaluable patients, 28 received peptichemio and 28 received L-PAM. There were no objective responses in the L-PAM group, and disease stabilized in four patients (14%). The median duration of stable disease was three months (range, 3-4 months). In the peptichemio group seven patients (25%) achieved a partial remission, one patient (3%) achieved less than partial remission and three patients (11%) had stable disease. The median duration of response was six months (range, 5-7+ months) for responding patients and three months (range, 2-5 months) for stable disease. The major toxicity of both drugs was myelosuppression which was cumulative. In conclusion, peptichemio is an active agent in advanced breast cancer, but L-PAM is ineffective in previously treated patients with metastatic breast cancer.

Sixty-two patients with breast cancer treated with Adriamycin-containing adjuvant chemotherapy developed recurrent disease. Four patients refused to take any form of systemic therapy at the time of relapse. Fifty-eight patients were managed with various treatment modalities, and of these 33 (57%) achieved on objective remission, 11 (19%) had stable disease and 14 patients (24%) did not respond to any form of therapy. Twenty-four patients received more than one treatment modality. Thirty-eight patients were treated with chemotherapy and 35 received endocrine therapy. Eight of 20 patients (40%) achieved objective remission upon retreatment with higher dose of 5-fluorouracil, Adriamycin, and cyclophosphamide at time of relapse, and seven of 18 patients (38%) treated with other chemotherapeutic agents showed objective remission. Fourteen of 35 patients (40%) achieved objective remission with hormonal therapies. The median survival from first relapse was 15 months for all patients, and was 25.7 months for responding patients. Survival was significantly longer in asymptomatic patients compared with those who were symptomatic from recurrent disease.

Forty-four patients with metastatic breast cancer who had previously received extensive conventional systemic therapy, including combination chemotherapy with doxorubicin, were treated with Bisantrene, a new anthracene derivative. The dose schedule was 250 to 300 mg/sq m body surface administered as a 1- to 2-hr i.v. infusion. Of 40 evaluable patients, there were nine partial responses, and 18 patients had stable disease. Responses were seen in all major sites of organ involvement with a median time to progression of 28 weeks. Moreover, responses were seen among patients who had either failed to respond or had demonstrated refractoriness to prior therapy with doxorubicin, suggesting an apparent lack of cross-resistance between doxorubicin and Bisantrene. Except for myelosuppression and one incidence of acute anaphylactoid reaction, Bisantrene was generally well tolerated by most patients. We believe that Bisantrene may ultimately have a major role in the effective treatment of metastatic breast cancer, and further clinical trials are warranted.

In an attempt to prolong the durations of remission and survival of patients with advanced breast cancer treated with the FAC-BCG protocol, we modified the CMF maintenance combination by increasing the dose of all three drugs and administering them intravenously. Eighty-five evaluable patients treated with this new regimen were compared with a recent historical control group of 105 evaluable patients treated with FAC-BCG and a lower-dose, oral CMF maintenance program. The overall (70% and 76%) and complete (16% and 19%) response rates were identical in these two groups. The median times to progression for all patients entered were similar too (13 months for both groups.). The durations of response were 17 months (PO-CMF) and 14 months (IV-CMF), not significantly different (P = .16). The durations of survival of the two treated groups were also very similar. After the administration of intensive FAC induction therapy, a high-dose, intravenous CMF maintenance program appears no better than a low-dose oral regimen. Other drug combinations consisting entirely of drugs not used in the induction regimen might be better choices for maintenance treatment